Patent Application
20190194760
The present invention relates to methods of diagnosing, monitoring of a subject or determining the prognosis of a subject. In particular, the invention relates to a method of determining the prognosis of a cancer patient comprising the steps (a) determining the expression level of at least one marker gene selected from the group consisting of the marker genes as described herein in a sample of the cancer patient to obtain a gene expression profile; (b) determining the prognosis of the cancer patient based on the gene expression profile obtained in step (a). In addition, the present invention refers to kits, diagnostic compositions devices and microarrays for determining at least one marker gene and uses thereof.
Technological advances have greatly increased our understanding of the molecular basis of diseases. In the past, biomarkers have been developed that can be used for a range of applications including predicting disease risk, diagnosis, predicting prognosis, identifying appropriate therapy for an individual, monitoring disease or for return of a disease, predicting the survival of a patient and other applications.
However, new diagnostic, prognostic and predictive biomarkers are necessary to improve disease prognosis and prediction.
In particular, in the treatment of cancer, for example lung cancer or prostate cancer, improved biomarkers are necessary. Lung cancer is the leading cause of cancer-related deaths world-wide and 85-90% of those malignancies are classified as non-small cell lung cancer (NSCLC). For decades, clinical outcomes of patients with advanced NSCLC were poor with 5-year survival rates of less than 5%. However, immunotherapeutic approaches, in particular checkpoint inhibitors, have recently dramatically impacted the field of cancer therapy. The aim of immunotherapy is to induce and activate host immune responses against the tumor. Antibodies blocking the interaction of inhibitory T cell receptors CTLA-4 or PD-1 with their ligands were demonstrated to improve survival rates in patients with metastasized melanoma and NSCLC. In addition, encouraging long lasting responses have been observed in a variety of solid tumors and hematologic malignancies after treatment with antibodies blocking PD-1 or PD-L1. Whereas these clinical results are highly encouraging, a substantial portion of patients fail to benefit from checkpoint inhibition treatment. Furthermore, immune-mediated adverse effects occur even in patients who do not respond to treatment.
Thus, there is a need for new biomarkers for prognosis and prediction in diseases, in particular in cancer, such as lung cancer or prostate cancer.
To address these need, the present invention relates to a method of diagnosing, monitoring of a subject or determining the prognosis of a subject comprising the steps of (a) determining the expression level of at least one marker gene selected from the group consisting of the genes set out in table 1 in a sample of the subject to obtain a gene expression profile; (b) diagnosing, monitoring of a subject or determining the prognosis of the subject based on the gene expression profile obtained in step (a).
In particular, the invention relates to a method of determining the prognosis of a cancer patient comprising the steps of
(a) determining the expression level of at least one marker gene selected from the group consisting of the marker genes set out in table 1 in a sample of the cancer patient to obtain a gene expression profile;
(b) determining the prognosis of the cancer patient based on the gene expression profile obtained in step (a).
In specific embodiments, the at least one marker gene is selected from the group consisting of genes set out in table 2. In preferred embodiments, the at least one marker gene is selected from the group consisting of marker genes set out in table 3. In more preferred embodiments, the at least one marker gene is selected from group consisting of marker genes set out in table 4. In even more preferred embodiments, the at least one marker gene is selected from group consisting of marker genes set out in table 5.
In specific embodiments, the at least one marker gene is selected from the group consisting of genes set out in table 2B. In preferred embodiments, the at least one marker gene is selected from the group consisting of marker genes set out in table 3B. In more preferred embodiments, the at least one marker gene is selected from group consisting of marker genes set out in table 4B. In even more preferred embodiments, the at least one marker gene is selected from group consisting of marker genes set out in table 5B.
In some embodiments at least 10 marker genes are selected from table 1. Preferably at least 30 marker genes, more preferably at least 50 marker genes, most preferably at least 100 marker genes are selected from table 1. In some embodiments at least 10 marker genes are selected from table 2; preferably at least 30 marker genes, more preferably at least 50 marker genes, most preferably at least 100 marker genes are selected from table 2. In other embodiments at least 10 genes are selected from table 3; preferably at least 30 marker genes, more preferably at least 50 marker genes are selected from table 3. In further embodiments at least 10 genes are selected from table 4. Preferably at least 20 marker genes, more preferably at least 30 marker genes are selected from table 4. In some embodiments at least 10 marker genes are selected from table 5.
In some embodiments at least 10 marker genes are selected from table 2B; preferably at least 30 marker genes, more preferably at least 50 marker genes, most preferably at least 90 marker genes are selected from table 2B. In other embodiments at least 10 genes are selected from table 3B; preferably at least 30 marker genes, more preferably at least 40 marker genes are selected from table 3B. In further embodiments at least 10 genes are selected from table 4B. Preferably at least 20 marker genes, more preferably at least 25 marker genes are selected from table 4B. In some embodiments at least 8 marker genes are selected from table 5B.
In specific embodiments, the gene expression profile of step (a) is obtained by determining the difference of the expression level of the at least one marker gene measured before administration of the therapeutic agent and after administration of at least one dose of the therapeutic agent.
Typically, the therapeutic agent is any agent used for therapy of a disease, preferably of cancer or tumor diseases. Preferably the therapeutic agent is an immunostimulatory composition and/or a vaccine and/or an immunotherapeutic agent.
In a preferred embodiment, the immunostimulatory composition and/or vaccine comprises at least one antigen selected from the group consisting of MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4. Preferably, the immunostimulatory composition and/or vaccine comprises the antigens MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4 or fragments or variants thereof.
Typically, the antigen(s) are present as peptides or proteins and/or are encoded by at least one nucleotide sequence. In preferred embodiments, the antigen(s) are encoded by at least one mRNA molecule.
The invention refers particularly to the prognosis of lung cancer, more particularly to non-small cell lung cancer (NSCLC).
Typically, the sample of the patient comprises peripheral blood mono-nuclear cells (PBMCs).
In some embodiments, in step (b) a hierarchical clustering algorithm is applied.
A further aspect of the invention relates to a kit, diagnostic composition or device for the analysis of at least one marker gene set out in table 1 comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene set out in table 1. The kit, diagnostic composition or device may further comprise an enzyme for primer elongation, nucleotides and/or labeling agents. Also contemplated is the use of said kit, diagnostic composition or device for determining the prognosis of a cancer patient.
A further aspect of the invention relates to a microarray, comprising at least one probe selective for determining the expression level of at least one marker gene set out in table 1 and the use of said microarray for determining the prognosis of a cancer patient.
More specifically, the invention refers to a method of determining the prognosis of a patient comprising the steps of
The inventor found out that by the 30 marker genes of table 4 is possible to classify cancer patients (
In specific embodiments further marker genes such as least 10 additional marker genes, preferably at least 20 additional marker genes, more preferably at least 70 additional marker genes are selected from table 1, table 2 or table 3 are employed for the determining the prognosis of the patient.
The invention further refers to a method of determining the prognosis of a patient comprising the steps of
The inventors found that the marker genes set out in tables 11 to 15 are particular suitable to classify both lung cancer and prostate cancer patients. Therefore, the patient may be cancer or tumor patient, in particular a lung cancer or prostate cancer patient. In a specific embodiment, the cancer patient is a NSCLC cancer or prostate cancer patient.
In specific embodiments the at least one marker genes is selected from the group consisting of marker genes set out in table 12, table 13, table 14 or table 15.
In specific embodiments least 10 marker genes, preferably at least 30 marker genes, more preferably at least 50 marker genes, most preferably at least 100 marker genes are selected from table 11 or table 12. In a further embodiment, at least 10 marker genes, preferably at least 30 marker genes, more preferably at least 50 marker genes are selected from table 13. In another embodiment at least 10 marker genes, preferably at least 20 marker genes, more preferably at least 30 marker genes are selected from the group consisting of from table 14.
In some embodiments, the expression level of at least one marker gene is measured before administration and/or after administration of at least one dose of a therapeutic agent. Typically, the therapeutic agent is an immunostimulatory composition and/or a vaccine and/or an immunotherapeutic agent. In one embodiment, the immunostimulatory composition and/or vaccine comprises at least one antigen selected from the group consisting of MAGE-C1, MAGE-C2, NY-ESO-1, Survivin, 5T4, PSA, PSMA, PSCA, STEAP, PAP and MUC1 or fragments or variants thereof. In a specific embodiment, the immunostimulatory composition and/or vaccine comprises the antigens (i) MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4 or fragments or variants thereof; or (ii) PSA, PSMA, PSCA, STEAP, PAP and MUC1 or fragments or variants thereof.
Accordingly, a further aspect of the invention refers to a kit, diagnostic composition or device for the analysis of at least one marker gene set out in table 11 comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene set out in table 11.
Another aspect refers to a microarray, comprising at least one probe selective for determining the expression level of at least one marker gene set out in table 11.
Another aspect of the invention refers to a method of determining the prognosis of a patient comprising the steps of
The inventors found that the marker genes set out in tables 6 to 10 are particularly suitable to classify prostate cancer patients. Accordingly, the patient may be a cancer or tumor patient, in particular a prostate cancer patient. Therefore, in one embodiment, the immunostimulatory composition and/or vaccine comprises at least one antigen selected from the group consisting of PSA, PSMA, PSCA, STEAP, PAP and MUC1 or fragments or variants thereof.
Accordingly, another aspect of the invention refers to a kit, diagnostic composition or device for the analysis of at least one marker gene set out in table 6 comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene set out in table 6.
An additional aspect refers to a microarray, comprising at least one probe selective for determining the expression level of at least one marker gene set out in table 6.
For the sake of clarity and readability, the following definitions are provided. Any technical feature mentioned for these definitions may be read on each and every embodiment of the invention. Additional definitions and explanations may be specifically provided in the context of these embodiments. Unless defined otherwise, all technical and scientific terms used herein generally have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Generally, the nomenclature used herein and the laboratory procedures in cell culture, molecular genetics, organic chemistry, and nucleic acid chemistry and hybridization are those well known and commonly employed in the art. Standard techniques are used for molecular biotechnology assays. The techniques and procedures are generally performed according to conventional methods in the art and various general references (e.g., Sambrook et al., 1989, Molecular Cloning: A Laboratory Manual, 2d ed. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.), which are provided throughout this document.
Marker, marker gene: The terms “marker” or “maker gene”, can be used interchangeably and relate to a gene, genetic unit or sequence (a nucleotide sequence or amino acid or protein sequence) as defined herein, the term also refers to any expression product of said genetic unit or sequence, in particular mRNA transcript, a polypeptide or protein encoded by the transcript or fragments thereof, as well as homologous derivatives thereof as described herein above. In particular, the term marker gene refers to a gene set out in table 1. Preferably, the marker gene is selected from the group consisting of genes set out in table 2, more preferably from the group consisting of genes set out in table 3, even more preferably from group consisting of genes set out in table 4, most preferably at least from group consisting of genes set out in table 5.
Subject, individual, patient: A subject, individual or patient according to the present invention is an animal, preferably a mammal, more preferably a human being. A subject, individual or patient according to the present invention is an animal, preferably a mammal, more preferably a human being. The method also relates to healthy subjects and to patients. In particular, the method of the invention refers to patients who are cancer or tumor patients. A cancer or tumor patient is a subject or individual who is diagnosed as having cancer or tumor.
non-small-cell lung cancer (NSCLC): non-small-cell lung cancer as used herein refers to the three main sub-types of non-small-cell lung cancer including, without being restricted thereto, squamous cell lung carcinoma, adenocarcinoma and large cell lung carcinoma.
determining the prognosis of a patient: The term “determining the prognosis of a patient” (and also indication specific terms such as “determining the prognosis of a cancer or tumor patient”) as used herein refers to the prediction of the course or outcome of a diagnosed or detected disease, e.g. during a certain period of time, before a treatment, during a treatment or after a treatment. The term also refers to a determination of chance of survival or recovery from the disease, as well as to a prediction of the expected survival time of a subject. A prognosis may, specifically, involve establishing the likelihood for survival of a subject during a period of time into the future, such as 6 months, 1 year, 2 years, 3 years, 5 years, 10 years or any other period of time. In a specific embodiment the prognosis may involve predicting the survival of a patient, i.e. whether the survival of a subject is shorter than or equal to a certain period of time, such as 6 months, 12 months or 15 months or any other period of time, or longer than a certain period of time, such as 6 months, 12 months, 15 months or 30 months or any other period of time. For example, the prognosis may involve a prediction whether the survival time of a cancer patient is equal or shorter than 15 months or whether the survival time of a cancer patient is longer than 15 months.
Obtain a gene expression profile: The gene expression profile is obtained by relating the expression level of the at least one marker gene to a reference value. The reference value may be for example the expression level of a control gene measured in the same sample of the individual. Alternatively, the reference value may be a control expression level derived from a healthy control sample or a sample from a pathological sample (of the disease of interest). The pathological sample may be for example from a patient with tumor or cancer (e.g. progressive tumor or non-progressive tumor). Alternatively, the reference value may be the expression level measured at a different time point in the same patient. The different time point may be a different treatment stage, e.g. before treatment, during treatment, after treatment, after the administration of a certain amount of treatment doses. The different time point may be any type of periodical time segment, such as one week, 2 weeks one months, 2, 3, 4, 5, 6, 7, 8, 10, 11 or 12 months, 1.5 years, 2, 3, 4, 5, 6, 7, 8, 9, 10 years ago. In a preferred embodiment the gene expression profile is obtained by relation of the expression level of the at least one marker gene after administration of at least one dose of therapeutic agent to the expression level of the at least one marker gene before administration of the therapeutic agent.
Monitoring: The term “monitoring” as used herein relates to the accompaniment of a diagnosed or detected disease or disorder, e.g. during a treatment procedure or during a certain period of time, typically during 2 months, 3 months, 4 months, 6 months, 1 year, 2 years, 3 years, 5 years, 10 years, or any other period of time, changes of these sates of disease may be detected by comparing the expression. The term “accompaniment” means that states of disease as defined herein above and, in particular level of the marker genes of the present invention in a sample are measured and a gene expression profile is obtained by comparison to a reference value in any type of periodical time segment, e.g. every week, every 2 weeks, every month, every 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12 month, every 1.5 year, every 2, 3, 4, 5, 6, 7, 8, 9 or 10 years, during any period of time, e.g. during 2 weeks, 3 weeks, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 months, 1.5, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15 or 20 years, respectively.
Diagnosing: The term “diagnosing” as used herein means that a patient or subject may be considered to be suffering from a disease. In particular, term “diagnosing” as used herein means that a patient or subject may be considered to be suffering from a disease based on the marker gen expression profile of the present invention. The term “diagnosing” also refers to the conclusion reached through that comparison process.
Reference gene: The term “reference gene” or “control gene” as used herein refers to any suitable gene, e.g. to any steadily expressed and continuously detectable gene, gene product, expression product, protein or protein variant in the organism of choice. The term also includes gene products such as expressed proteins, peptides, polypeptides, as well as modified variants thereof. The invention hence also includes reference proteins derived from a reference gene. Also encompassed are all kinds of transcripts derivable from the reference gene as well as modifications thereof or secondary parameters linked thereto. Alternatively, or additionally, other reference parameters may also be used for reference purposes, e.g. metabolic concentrations, cell sizes etc.
Microarray: A (DNA) microarray (also commonly known as DNA chip or biochip) is a collection of microscopic DNA spots attached to a solid surface. DNA microarrays are used to measure the expression levels of large numbers of genes simultaneously or to genotype multiple regions of a genome. Each DNA spot contains picomoles (10-12 moles) of a specific DNA sequence, known as probes (or reporters or oligos). These can be a short section of a gene or other DNA element that are used to hybridize a nucleic acid sample (called target) under high-stringency conditions. Probe-target hybridization is usually detected and quantified by detection of fluorophore-, silver-, or chemiluminescence-labeled targets to determine relative abundance of nucleic acid sequences in the target. A “microarray” is a linear or two-dimensional array of discrete regions, each having a defined area, formed on the surface of a generally solid support such as, but not limited to, glass, plastic, or synthetic membrane. The density of the discrete regions on a microarray is determined by the total numbers of immobilized oligonucleotides to be detected on the surface of a single solid phase support, such as at least about 50/cm2, at least about 100/cm2, at least about 500/cm2, but below about 1,000/cm2 in some embodiments. The arrays may contain less than about 500, about 1000, about 1500, about 2000, about 2500, or about 3000 immobilized oligonucleotides in total. As used herein, a DNA microarray is an array of nucleic acids e.g. oligonucleotides or oligonucleotides placed on a chip or other surfaces used to hybridize to amplified or cloned oligonucleotides from a sample. Because the position of each particular group of oligonucleotides in the array is known, the identities of a sample oligonucleotides can be determined based on their binding to a particular position in the microarray.
Probe: In molecular biology, a hybridization probe is a fragment of DNA or RNA of variable length. It can be used in DNA or RNA samples to detect the presence of nucleotide sequences (the target) that are complementary to the nucleic acid sequence in the probe. The probe thereby hybridizes to single-stranded nucleic acid (DNA or RNA) whose base sequence allows probe-target base pairing due to complementarity between the probe and target.
Amplify: The term “amplify” is used in the broad sense to mean creating an amplification product can be made enzymatically with DNA or RNA polymerases. “Amplification,” as used herein, generally refers to the process of producing multiple copies of a desired sequence, particularly those of a sample. “Multiple copies” mean at least 2 copies. A “copy” does not necessarily mean perfect sequence complementarity or identity to the template sequence. It is possible to further use any sequencing method known in the art to identify the sequences of marker genes.
Protein: A protein typically comprises one or more peptides or polypeptides. A protein is typically folded into a 3-dimensional form, which may be required for the protein to exert its biological function. The sequence of a protein or peptide is typically understood to be the order, i.e. the succession of its amino acids.
Peptide: A peptide or polypeptide is typically a polymer of amino acid monomers, linked by peptide bonds. It typically contains less than 50 monomer units. Nevertheless, the term peptide is not a disclaimer for molecules having more than 50 monomer units. Long peptides are also called polypeptides, typically having between 50 and 600 monomeric units.
Fragment or part of a protein: Fragments or parts of a protein in the context of the present invention are typically understood to be peptides corresponding to a continuous part of the amino acid sequence of a protein, preferably having a length of about 6 to about 20 or even more amino acids, e.g. parts as processed and presented by MHC class I molecules, preferably having a length of about 8 to about 10 amino acids, e.g. 8, 9, or 10, (or even 11, or 12 amino acids), or fragments as processed and presented by MHC class II molecules, preferably having a length of about 13 or more amino acids, e.g. 13, 14, 15, 16, 17, 18, 19, 20 or even more amino acids, wherein these fragments may be selected from any part of the amino acid sequence. These fragments are typically recognized by T cells in form of a complex consisting of the peptide fragment and an MHC molecule, i.e. the fragments are typically not recognized in their native form. Fragments or parts of the proteins as defined herein may also comprise epitopes or functional sites of those proteins. Preferably, fragments or parts of a proteins in the context of the invention are antigens, particularly immunogens, e.g. antigen determinants (also called ‘epitopes’), or do have antigenic characteristics, eliciting an adaptive immune response. Therefore, fragments of proteins or peptides may comprise at least one epitope of those proteins or peptides. Furthermore, also domains of a protein, like the extracellular domain, the intracellular domain or the transmembrane domain, and shortened or truncated versions of a protein may be understood to comprise a fragment of a protein.
RNA, mRNA: RNA is the usual abbreviation for ribonucleic acid. It is a nucleic acid molecule, i.e. a polymer consisting of nucleotide monomers. These nucleotides are usually adenosine-monophosphate, uridine-monophosphate, guanosine-monophosphate and cytidine-monophosphate monomers, which are connected to each other along a so-called backbone. The backbone is formed by phosphodiester bonds between the sugar, i.e. ribose, of a first and a phosphate moiety of a second, adjacent monomer. The specific order of the monomers, i.e. the order of the bases linked to the sugar/phosphate-backbone, is called the RNA-sequence. Usually RNA may be obtainable by transcription of a DNA-sequence, e.g., inside a cell. In eukaryotic cells, transcription is typically performed inside the nucleus or the mitochondria. In vivo, transcription of DNA usually results in the so-called premature RNA, which has to be processed into so-called messenger-RNA, usually abbreviated as mRNA. Processing of the premature RNA, e.g. in eukaryotic organisms, comprises a variety of different posttranscriptional-modifications such as splicing, 5′-capping, polyadenylation, export from the nucleus or the mitochondria and the like. The sum of these processes is also called maturation of RNA. The mature messenger RNA usually provides the nucleotide sequence that may be translated into an amino acid sequence of a particular peptide or protein. Typically, a mature mRNA comprises a 5′-cap, optionally a 5′UTR, an open reading frame, optionally a 3′UTR and a poly(A) sequence. Aside from messenger RNA, several non-coding types of RNA exist which may be involved in regulation of transcription and/or translation, and immunostimulation. The term “RNA” further encompass other coding RNA molecules, such as viral RNA, retroviral RNA and replicon RNA, small interfering RNA (siRNA), antisense RNA, CRISPR RNA, ribozymes, aptamers, riboswitches, immunostimulating RNA, transfer RNA (tRNA), ribosomal RNA (rRNA), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), microRNA (miRNA), and Piwi-interacting RNA (piRNA).
DNA: DNA is the usual abbreviation for deoxyribonucleic acid. It is a nucleic acid molecule, i.e. a polymer consisting of nucleotide monomers. These nucleotides are usually deoxy-adenosine-monophosphate, deoxy-thymidine-monophosphate, deoxy-guanosine-monophosphate and deoxy-cytidine-monophosphate monomers which are—by themselves—composed of a sugar moiety (deoxyribose), a base moiety and a phosphate moiety, and polymerized by a characteristic backbone structure. The backbone structure is, typically, formed by phosphodiester bonds between the sugar moiety of the nucleotide, i.e. deoxyribose, of a first and a phosphate moiety of a second, adjacent monomer. The specific order of the monomers, i.e. the order of the bases linked to the sugar/phosphate-backbone, is called the DNA-sequence. DNA may be single-stranded or double-stranded. In the double stranded form, the nucleotides of the first strand typically hybridize with the nucleotides of the second strand, e.g. by A/T-base-pairing and G/C-base-pairing.
Sequence of a nucleic acid molecule/nucleic acid sequence: The sequence of a nucleic acid molecule is typically understood to be the particular and individual order, i.e. the succession of its nucleotides.
Sequence of amino acid molecules/amino acid sequence: The sequence of a protein or peptide is typically understood to be the order, i.e. the succession of its amino acids.
Vaccine: A vaccine is a biological preparation that provides active acquired immunity to a particular disease. A vaccine typically contains an agent comprising an antigen which induces an adaptive immune response.
Immunotherapeutic agents: The term immunotherapeutic agent refers to agents capable of modulating the components of the immune system. Examples of immunotherapeutic agents are without limitation dendritic cells, T cells, antibodies, checkpoint modulators or cytokines, chemokines, interleukins, immunostimulatory agents and adjuvants. Immunotherapeutic agents include checkpoint modulators, therapeutic antibodies, immune cell therapy, T cell receptors (including CAR T cell therapy), immune system modulators such as cytokines and chemokines and vaccines.
Antigen: In the context of the present invention “antigen” refers typically to a substance, which may be recognized by the immune system, preferably by the adaptive immune system, and is capable of triggering an antigen-specific immune response, e.g. by formation of antibodies and/or antigen-specific T cells as part of an adaptive immune response. Typically, an antigen may be or may comprise a peptide or protein which may be presented by the MHC to T-cells and comprises at least one epitope. In particular, the antigen may be a pathogenic antigen or a tumor antigen.
Tumor antigens: In a further embodiment, the mRNA according to the present invention may encode a protein or a peptide, which comprises a peptide or protein comprising a tumor antigen, a fragment, variant or derivative of said tumor antigen, preferably, wherein the tumor antigen is a melanocyte-specific antigen, a cancer-testis antigen or a tumor-specific antigen, preferably a CT-X antigen, a non-X CT-antigen, a binding partner for a CT-X antigen or a binding partner for a non-X CT-antigen or a tumor-specific antigen, more preferably a CT-X antigen, a binding partner for a non-X CT-antigen or a tumor-specific antigen or a fragment, variant or derivative of said tumor antigen; and wherein each of the nucleic acid sequences encodes a different peptide or protein; and wherein at least one of the nucleic acid sequences encodes for 1A01_HLA-A/m; 1A02; 5T4; ACRBP; AFP; AKAP4; alpha-actinin-_4/m; alpha-methylacyl-coenzyme_A_racemase; ANDR; ART-4; ARTC1/m; AURKB; B2MG; B3GN5; B4GN1; B7H4; BAGE-1; BASI; BCL-2; bcr/abl; beta-catenin/m; BING-4; BIRC7; BRCA1/m; BY55; calreticulin; CAMEL; CASP-8/m; CASPA; cathepsin_B; cathepsin_L; CD1A; CD1B; CD1C; CD1D; CD1E; CD20; CD22; CD276; CD33; CD3E; CD3Z; CD44_Isoform_1; CD44_Isoform_6; CD4; CD52; CD55; CD56; CD80; CD86; CD8A; CDC27/m; CDE30; CDK4/m; CDKN2A/m; CEA; CEAM6; CH3L2; CLCA2; CML28; CML66; COA-1/m; coactosin-like_protein; collagen_XXIII; COX-2; CP1B1; CSAG2; CT45A1; CT55; CT-_9/BRD6; CTAG2_Isoform_LAGE-1A; CTAG2_Isoform_LAGE-1B; CTCFL; Cten; cyclin_B1; cyclin_D1; cyp-B; DAM-10; DEP1A; E7; EF1A2; EFTUD2/m; EGFR; EGLN3; ELF2/m; EMMPRIN; EpCam; EphA2; EphA3; ErbB3; ERBB4; ERG; ETV6; EWS; EZH2; FABP7; FCGR3A_Version_1; FCGR3A_Version_2; FGF5; FGFR2; fibronectin; FOS; FOXP3; FUT1; G250; GAGE-1; GAGE-2; GAGE-3; GAGE-4; GAGE-5; GAGE-6; GAGE7b; GAGE-8_(GAGE-2D); GASR; GnT-V; GPC3; GPNMB/m; GRM3; HAGE; hepsin; Her2/neu; HLA-A2/m; homeobox_NKX3.1; HOM-TES-85; HPG1; HS71A; HS71B; HST-2; hTERT; iCE; IF2B3; IL10; IL-13Ra2; IL2-RA; IL2-RB; IL2-RG; IL-5; IMP3; ITA5; ITB1; ITB6; kallikrein-2; kallikrein-4; KI20A; KIAA0205; KIF2C; KK-LC-1; LDLR; LGMN; LIRB2; LY6K; MAGA5; MAGA8; MAGAB; MAGE-A10; MAGE-A12; MAGE-A1; MAGE-A2; MAGE-A3; MAGE-A4; MAGE-A6; MAGE-A9; MAGE-B10; MAGE-B16; MAGE-B17; MAGE-B1; MAGE-B2; MAGE-B3; MAGE-B4; MAGE-B5; MAGE-B6; MAGE-C1; MAGE-C2; MAGE-C3; MAGE-D1; MAGE-D2; MAGE-D4; MAGE-_E1; MAGE-E1_(MAGE1); MAGE-E2; MAGE-F1; MAGE-H1; MAGEL2; mammaglobin_A; MART-1/melan-A; MART-2; MC1_R; M-CSF; mesothelin; MITF; MMP1_1; MMP7; MUC-1; MUM-1/m; MUM-2/m; MYCN; MYO1A; MYO1B; MYO1C; MYO1D; MYO1E; MYO1F; MYO1G; MYO1H; NA17; NA88-A; Neo-PAP; NFYC/m; NGEP; NPM; NRCAM; NSE; NUF2; NY-ESO-1; OA1; OGT; OS-9; osteocalcin; osteopontin; p53; PAGE-4; PAI-1; PAI-2; PAP; PATE; PAX3; PAX5; PD1L1; PDCD1; PDEF; PECA1; PGCB; PGFRB; Pim-1_-Kinase; Pin-1; PLAC1; PMEL; PML; POTEF; POTE; PRAME; PRDX5/m; PRM2; prostein; proteinase-3; PSA; PSB9; PSCA; PSGR; PSM; PTPRC; RAB8A; RAGE-1; RARA; RASH; RASK; RASN; RGS5; RHAMM/CD168; RHOC; RSSA; RU1; RU2; RUNX1; S-100; SAGE; SART-_1; SART-2; SART-3; SEPR; SERPINB5; SIA7F; SIA8A; SIAT9; SIRT2/m; SOX10; SP17; SPNXA; SPXN3; SSX-1; SSX-2; SSX3; SSX-4; ST1A1; STAG2; STAMP-1; STEAP-1; Survivin-2B; survivin; SYCP1; SYT-SSX-1; SYT-SSX-2; TARP; TCRg; TF2AA; TGFB1; TGFR2; TGM-4; TIE2; TKTL1; TPI/m; TRGV11; TRGV9; TRPC1; TRP-p8; TSG10; TSPY1; TVC_(TRGV3); TX101; tyrosinase; TYRP1; TYRP2; UPA; VEGFR1; WT1; and XAGE1, and a immunoglobulin idiotype of a lymphoid blood cell or a T cell receptor idiotype of a lymphoid blood cell, or a fragment, variant or derivative of said tumor antigen; preferably survivin or a homologue thereof, an antigen from the MAGE-family or a binding partner thereof or a fragment, variant or derivative of said tumor antigen.
Particularly preferred in this context are the tumor antigens NY-ESO-1, 5T4, MAGE-C1, MAGE-C2, Survivin, Muc-1, PSA, PSMA, PSCA, STEAP and PAP.
Most preferred is the combination of the antigens NY-ESO-1, 5T4, MAGE-C1, MAGE-C2, and Survivin.
Therapeutic proteins: Therapeutic proteins as defined herein are peptides or proteins which are beneficial for the treatment of any inherited or acquired disease or which improves the condition of an individual. Particularly, therapeutic proteins plays a big role in the creation of therapeutic agents that could modify and repair genetic errors, destroy cancer cells or pathogen infected cells, treat immune system disorders, treat metabolic or endocrine disorders, among other functions. Furthermore adjuvant proteins, therapeutic antibodies are encompassed by therapeutic proteins and also hormone replacement therapy which is e.g. used in the therapy of women in the menopause. In newer approaches somatic cells of a patient are used to reprogram them into pluripotent stem cells which replace the disputed stem cell therapy. Also these proteins used for reprogramming of somatic cells or used for differentiating of stem cells are defined herein as therapeutic proteins. Furthermore therapeutic proteins may be used for other purposes e.g. wound healing, tissue regeneration, angiogenesis, etc.
Therefore therapeutic proteins can be used for various purposes including treatment of various diseases like e.g. infectious diseases, neoplasms (e.g. cancer or tumor diseases), diseases of the blood and blood-forming organs, endocrine, nutritional and metabolic diseases, diseases of the nervous system, diseases of the circulatory system, diseases of the respiratory system, diseases of the digestive system, diseases of the skin and subcutaneous tissue, diseases of the musculoskeletal system and connective tissue, and diseases of the genitourinary system, independently if they are inherited or acquired.
These and other proteins are understood to be therapeutic, as they are meant to treat the subject by replacing its defective endogenous production of a functional protein in sufficient amounts. Accordingly, such therapeutic proteins are typically mammalian, in particular human proteins.
Furthermore, adjuvant or immunostimulating proteins are also encompassed in the term therapeutic proteins. Adjuvant or immunostimulating proteins may be used in this context to induce, alter or improve an immune response in an individual to treat a particular disease or to ameliorate the condition of the individual.
In this context, adjuvant proteins may be selected from mammalian, in particular human adjuvant proteins, which typically comprise any human protein or peptide, which is capable of eliciting an innate immune response (in a mammal), e.g. as a reaction of the binding of an exogenous TLR ligand to a TLR. More preferably, human adjuvant proteins are selected from the group consisting of proteins, which are components and ligands of the signalling networks of the pattern recognition receptors including TLR, NLR and RLH, including TLR1, TLR2, TLR3, TLR4, TLR5, TLR6, TLR7, TLR8, TLR9, TLR10, TLR11; NOD1, NOD2, NOD3, NOD4, NOD5, NALP1, NALP2, NALP3, NALP4, NALP5, NALP6, NALP6, NALP7, NALP7, NALP8, NALP9, NALP10, NALP11, NALP12, NALP13, NALP14,1 IPAF, NAIP, CIITA, RIG-I, MDA5 and LGP2, the signal transducers of TLR signaling including adaptor proteins including e.g. Trif and Cardif; components of the Small-GTPases signalling (RhoA, Ras, Rac1, Cdc42, Rab etc.), components of the PIP signalling (PI3K, Src-Kinases, etc.), components of the MyD88-dependent signalling (MyD88, IRAK1, IRAK2, IRAK4, TIRAP, TRAF6 etc.), components of the MyD88-independent signalling (TICAM1, TICAM2, TRAF6, TBK1, IRF3, TAK1, IRAK1 etc.); the activated kinases including e.g. Akt, MEKK1, MKK1, MKK3, MKK4, MKK6, MKK7, ERK1, ERK2, GSK3, PKC kinases, PKD kinases, GSK3 kinases, JNK, p38MAPK, TAK1, IKK, and TAK1; the activated transcription factors including e.g. NF-kB, c-Fos, c-Jun, c-Myc, CREB, AP-1, Elk-1, ATF2, IRF-3, IRF-7.
Mammalian, in particular human adjuvant proteins may furthermore be selected from the group consisting of heat shock proteins, such as HSP10, HSP60, HSP65, HSP70, HSP75 and HSP90, gp96, Fibrinogen, TypIII repeat extra domain A of fibronectin; or components of the complement system including C1q, MBL, C1r, C1s, C2b, Bb, D, MASP-1, MASP-2, C4b, C3b, C5a, C3a, C4a, C5b, C6, C7, C8, C9, CR1, CR2, CR3, CR4, C1qR, C1INH, C4 bp, MCP, DAF, H, I, P and CD59, or induced target genes including e.g. Beta-Defensin, cell surface proteins; or human adjuvant proteins including trif, flt-3 ligand, Gp96 or fibronectin, etc., or any species homolog of any of the above human adjuvant proteins.
Mammalian, in particular human adjuvant proteins may furthermore comprise cytokines which induce or enhance an innate immune response, including IL-1 alpha, IL1 beta, IL-2, IL-6, IL-7, IL-8, IL-9, IL-12, IL-13, IL-15, IL-16, IL-17, IL-18, IL-21, IL-23, TNFalpha, IFNalpha, IFNbeta, IFNgamma, GM-CSF, G-CSF, M-CSF; chemokines including IL-8, IP-10, MCP-1, MIP-1alpha, RANTES, Eotaxin, CCL21; cytokines which are released from macrophages, including IL-1, IL-6, IL-8, IL-12 and TNF-alpha; as well as IL-1R1 and IL-1 alpha.
Therapeutic proteins for the treatment of blood disorders, diseases of the circulatory system, diseases of the respiratory system, cancer or tumor diseases, infectious diseases or immunedeficiencies or adjuvant proteins are typically proteins of mammalian origin, preferably of human origin, depending on which animal shall be treated. A human subject, for example, is preferably treated by a therapeutic protein of human origin.
Pathogenic adjuvant proteins, typically comprise a pathogenic adjuvant protein, which is capable of eliciting an innate immune response (in a mammal), more preferably selected from pathogenic adjuvant proteins derived from bacteria, protozoa, viruses, or fungi, etc., e.g., bacterial (adjuvant) proteins, protozoan (adjuvant) proteins (e.g. profilin-like protein of Toxoplasma gondii), viral (adjuvant) proteins, or fungal (adjuvant) proteins, etc.
Particularly, bacterial (adjuvant) proteins may be selected from the group consisting of bacterial heat shock proteins or chaperons, including Hsp60, Hsp70, Hsp90, Hsp100; OmpA (Outer membrane protein) from gram-negative bacteria; bacterial porins, including OmpF; bacterial toxins, including pertussis toxin (PT) from Bordetella pertussis, pertussis adenylate cyclase toxin CyaA and CyaC from Bordetella pertussis, PT-9K/129G mutant from pertussis toxin, pertussis adenylate cyclase toxin CyaA and CyaC from Bordetella pertussis, tetanus toxin, cholera toxin (CT), cholera toxin B-subunit, CTK63 mutant from cholera toxin, CTE112K mutant from CT, Escherichia coli heat-labile enterotoxin (LT), B subunit from heat-labile enterotoxin (LTB) Escherichia coli heat-labile enterotoxin mutants with reduced toxicity, including LTK63, LTR72; phenol-soluble modulin; neutrophil-activating protein (HP-NAP) from Helicobacter pylori; Surfactant protein D; Outer surface protein A lipoprotein from Borrelia burgdorferi, Ag38 (38 kDa antigen) from Mycobacterium tuberculosis; proteins from bacterial fimbriae; Enterotoxin CT of Vibrio cholerae, Pilin from pili from gram negative bacteria, and Surfactant protein A; etc., or any species homolog of any of the above bacterial (adjuvant) proteins.
Bacterial (adjuvant) proteins may also comprise bacterial flagellins. In the context of the present invention, bacterial flagellins may be selected from flagellins from organisms including, without being limited thereto, Agrobacterium, Aquifex, Azospirillum, Bacillus, Bartonella, Bordetella, Borrelia, Burkholderia, Campylobacter, Caulobacte, Clostridium, Escherichia, Helicobacter, Lachnospiraceae, Legionella, Listeria, Proteus, Pseudomonas, Rhizobium, Rhodobacter, Roseburia, Salmonella, Serpulina, Serratia, Shigella, Treponema, Vibrio, Wolinella, Yersinia, more preferably from flagellins from the species including, without being limited thereto, Agrobacterium tumefaciens, Aquifex pyrophilus, Azospirillum brasilense, Bacillus subtilis, Bacillus thuringiensis, Bartonella bacilliformis, Bordetella bronchiseptica, Borrelia burgdorferi, Burkholderia cepacia, Campylobacter jejuni, Caulobacter crescentus, Clostridium botulinum strain Bennett clone 1, Escherichia coli, Helicobacter pylori, Lachnospiraceae bacterium, Legionella pneumophila, Listeria monocytogenes, Proteus mirabilis, Pseudomonas aeroguinosa, Pseudomonas syringae, Rhizobium meliloti, Rhodobacter sphaeroides, Roseburia cecicola, Roseburis hominis, Salmonella typhimurium, Salmonella bongori, Salmonella typhi, Salmonella enteritidis, Serpulina hyodysenteriae, Serratia marcescens, Shigella boydii, Treponema phagedenis, Vibrio alginolyticus, Vibrio cholerae, Vibrio parahaemolyticus, Wolinella succinogenes and Yersinia enterocolitica.
Protozoan (adjuvant) proteins are a further example of pathogenic adjuvant proteins. Protozoan (adjuvant) proteins may be selected in this context from any protozoan protein showing adjuvant properties, more preferably, from the group consisting of, without being limited thereto, Tc52 from Trypanosoma cruzi, PFTG from Trypanosoma gondii, Protozoan heat shock proteins, LeIF from Leishmania spp., profiling-like protein from Toxoplasma gondii, etc.
Viral (adjuvant) proteins are another example of pathogenic adjuvant proteins. In this context, viral (adjuvant) proteins may be selected from any viral protein showing adjuvant properties, more preferably, from the group consisting of, without being limited thereto, Respiratory Syncytial Virus fusion glycoprotein (F-protein), envelope protein from MMT virus, mouse leukemia virus protein, Hemagglutinin protein of wild-type measles virus, etc.
Fungal (adjuvant) proteins are even a further example of pathogenic adjuvant proteins. In the context of the present invention, fungal (adjuvant) proteins may be selected from any fungal protein showing adjuvant properties, more preferably, from the group consisting of, fungal immunomodulatory protein (FIP; LZ-8), etc.
Finally, adjuvant proteins may furthermore be selected from the group consisting of, Keyhole limpet hemocyanin (KLH), OspA, etc.
As mentioned above, also therapeutic antibodies are defined herein as therapeutic proteins. These therapeutic antibodies are preferably selected from antibodies, which are used inter alia for the treatment of cancer or tumor diseases, e.g. 131I-tositumomab (Follicular lymphoma, B cell lymphomas, leukemias), 3F8 (Neuroblastoma), 8H9, Abagovomab (Ovarian cancer), Adecatumumab (Prostate and breast cancer), Afutuzumab (Lymphoma), Alacizumab pegol, Alemtuzumab (B-cell chronic lymphocytic leukaemia, T-cell-Lymphoma), Amatuximab, AME-133v (Follicular lymphoma, cancer), AMG 102 (Advanced Renal Cell Carcinoma), Anatumomab mafenatox (Non-small cell lung carcinoma), Apolizumab (Solid Tumors, Leukemia, Non-Hodgkin-Lymphoma, Lymphoma), Bavituximab (Cancer, viral infections), Bectumomab (Non-Hodgkin's lymphoma), Belimumab (Non-Hodgkin lymphoma), Bevacizumab (Colon Cancer, Breast Cancer, Brain and Central Nervous System Tumors, Lung Cancer, Hepatocellular Carcinoma, Kidney Cancer, Breast Cancer, Pancreatic Cancer, Bladder Cancer, Sarcoma, Melanoma, Esophageal Cancer; Stomach Cancer, Metastatic Renal Cell Carcinoma; Kidney Cancer, Glioblastoma, Liver Cancer, Proliferative Diabetic Retinopathy, Macular Degeneration), Bivatuzumab mertansine (Squamous cell carcinoma), Blinatumomab, Brentuximab vedotin (Hematologic cancers), Cantuzumab (Colon Cancer, Gastric Cancer, Pancreatic Cancer, NSCLC), Cantuzumab mertansine (Colorectal cancer), Cantuzumab ravtansine (Cancers), Capromab pendetide (Prostate cancer), Carlumab, Catumaxomab (Ovarian Cancer, Fallopian Tube Neoplasms, Peritoneal Neoplasms), Cetuximab (Metastatic colorectal cancer and head and neck cancer), Citatuzumab bogatox (Ovarian cancer and other solid tumors), Cixutumumab (Solid tumors), Clivatuzumab tetraxetan (Pancreatic cancer), CNTO 328 (B-Cell Non-Hodgkin's Lymphoma, Multiple Myeloma, Castleman's Disease, ovarian cancer), CNTO 95 (Melanoma), Conatumumab, Dacetuzumab (Hematologic cancers), Dalotuzumab, Denosumab (Myeloma, Giant Cell Tumor of Bone, Breast Cancer, Prostate Cancer, Osteoporosis), Detumomab (Lymphoma), Drozitumab, Ecromeximab (Malignant melanoma), Edrecolomab (Colorectal carcinoma), Elotuzumab (Multiple myeloma), Elsilimomab, Enavatuzumab, Ensituximab, Epratuzumab (Autoimmune diseases, Systemic Lupus Erythematosus, Non-Hodgkin-Lymphoma, Leukemia), Ertumaxomab (Breast cancer), Ertumaxomab (Breast Cancer), Etaracizumab (Melanoma, prostate cancer, ovarian cancer), Farletuzumab (Ovarian cancer), FBTA05 (Chronic lymphocytic leukaemia), Ficlatuzumab (Cancer), Figitumumab (Adrenocortical carcinoma, non-small cell lung carcinoma), Flanvotumab (Melanoma), Galiximab (B-cell lymphoma), Galiximab (Non-Hodgkin-Lymphoma), Ganitumab, GC1008 (Advanced Renal Cell Carcinoma; Malignant Melanoma, Pulmonary Fibrosis), Gemtuzumab (Leukemia), Gemtuzumab ozogamicin (Acute myelogenous leukemia), Girentuximab (Clear cell renal cell carcinoma), Glembatumumab vedotin (Melanoma, breast cancer), GS6624 (Idiopathic pulmonary fibrosis and solid tumors), HuC242-DM4 (Colon Cancer, Gastric Cancer, Pancreatic Cancer), HuHMFG1 (Breast Cancer), HuN901-DM1 (Myeloma), Ibritumomab (Relapsed or refractory low-grade, follicular, or transformed B-cell non-Hodgkin's lymphoma (NHL)), Icrucumab, ID09C3 (Non-Hodgkin-Lymphoma), Indatuximab ravtansine, Inotuzumab ozogamicin, Intetumumab (Solid tumors (Prostate cancer, melanoma)), Ipilimumab (Sarcoma, Melanoma, Lung cancer, Ovarian Cancer leucemia, Lymphoma, Brain and Central Nervous System Tumors, Testicular Cancer, Prostate Cancer, Pancreatic Cancer, Breast Cancer), Iratumumab (Hodgkin's lymphoma), Labetuzumab (Colorectal cancer), Lexatumumab, Lintuzumab, Lorvotuzumab mertansine, Lucatumumab (Multiple myeloma, non-Hodgkin's lymphoma, Hodgkin's lymphoma), Lumiliximab (Chronic lymphocytic leukemia), Mapatumumab (Colon Cancer, Myeloma), Matuzumab (Lung Cancer, Cervical Cancer, Esophageal Cancer), MDX-060 (Hodgkin-Lymphoma, Lymphoma), MEDI 522 (Solid Tumors, Leukemia, Lymphoma, Small Intestine Cancer, Melanoma), Mitumomab (Small cell lung carcinoma), Mogamulizumab, MORab-003 (Ovarian Cancer, Fallopian Tube Cancer, Peritoneal Cancer), MORab-009 (Pancreatic Cancer, Mesothelioma, Ovarian Cancer, Non-Small Cell Lung Cancer, Fallopian Tube Cancer, Peritoneal Cavity Cancer), Moxetumomab pasudotox, MT103 (Non-Hodgkin-Lymphoma), Nacolomab tafenatox (Colorectal cancer), Naptumomab estafenatox (Non-small cell lung carcinoma, renal cell carcinoma), Narnatumab, Necitumumab (Non-small cell lung carcinoma), Nimotuzumab (Squamous cell carcinoma, head and neck cancer, nasopharyngeal cancer, glioma), Nimotuzumab (Squamous cell carcinomas, Glioma, Solid Tumors, Lung Cancer), Olaratumab, Onartuzumab (Cancer), Oportuzumab monatox, Oregovomab (Ovarian cancer), Oregovomab (Ovarian Cancer, Fallopian Tube Cancer, Peritoneal Cavity Cancer), PAM4 (Pancreatic Cancer), Panitumumab (Colon Cancer, Lung Cancer, Breast Cancer; Bladder Cancer; Ovarian Cancer), Patritumab, Pemtumomab, Pertuzumab (Breast Cancer, Ovarian Cancer, Lung Cancer, Prostate Cancer), Pritumumab (Brain cancer), Racotumomab, Radretumab, Ramucirumab (Solid tumors), Rilotumumab (Solid tumors), Rituximab (Urticaria, Rheumatoid Arthritis, Ulcerative Colitis, Chronic Focal Encephalitis, Non-Hodgkin-Lymphoma, Lymphoma, Chronic Lymphocytic Leukemia), Robatumumab, Samalizumab, SGN-30 (Hodgkin-Lymphoma, Lymphoma), SGN-40 (Non-Hodgkin-Lymphoma, Myeloma, Leukemia, Chronic Lymphocytic Leukemia), Sibrotuzumab, Siltuximab, Tabalumab (B-cell cancers), Tacatuzumab tetraxetan, Taplitumomab paptox, Tenatumomab, Teprotumumab (Hematologic tumors), TGN1412 (Chronic lymphocytic leukemia, rheumatoid arthritis), Ticilimumab (=tremelimumab), Tigatuzumab, TNX-650 (Hodgkin's lymphoma), Tositumomab (Follicular lymphoma, B cell lymphomas, Leukemias, Myeloma), Trastuzumab (Breast Cancer, Endometrial Cancer, Solid Tumors), TRBS07 (Melanoma), Tremelimumab, TRU-016 (Chronic lymphocytic leukemia), TRU-016 (Non-Hodgkin lymphoma), Tucotuzumab celmoleukin, Ublituximab, Urelumab, Veltuzumab (Non-Hodgkin's lymphoma), Veltuzumab (IMMU-106) (Non-Hodgkin's lymphoma), Volociximab (Renal Cell Carcinoma, Pancreatic Cancer, Melanoma), Votumumab (Colorectal tumors), WX-G250 (Renal Cell Carcinoma), Zalutumumab (Head and Neck Cancer, Squamous Cell Cancer), and Zanolimumab (T-Cell-Lymphoma);
Epitope: Epitopes (also called ‘antigen determinant’) can be distinguished in T cell epitopes and B cell epitopes. T cell epitopes or parts of the proteins in the context of the present invention may comprise fragments preferably having a length of about 6 to about 20 or even more amino acids, e.g. fragments as processed and presented by MHC class I molecules, preferably having a length of about 8 to about 10 amino acids, e.g. 8, 9, or 10, (or even 11, or 12 amino acids), or fragments as processed and presented by MHC class II molecules, preferably having a length of about 13 or more amino acids, e.g. 13, 14, 15, 16, 17, 18, 19, 20 or even more amino acids, wherein these fragments may be selected from any part of the amino acid sequence. These fragments are typically recognized by T cells in form of a complex consisting of the peptide fragment and an MHC molecule, i.e. the fragments are typically not recognized in their native form. B cell epitopes are typically fragments located on the outer surface of (native) protein or peptide antigens as defined herein, preferably having 5 to 15 amino acids, more preferably having 5 to 12 amino acids, even more preferably having 6 to 9 amino acids, which may be recognized by antibodies, i.e. in their native form.
Such epitopes of proteins or peptides may furthermore be selected from any of the herein mentioned variants of such proteins or peptides. In this context, antigenic determinants can be conformational or discontinuous epitopes, which are composed of segments of the proteins or peptides as defined herein that are discontinuous in the amino acid sequence of the proteins or peptides as defined herein, but are brought together in the three-dimensional structure or continuous or linear epitopes, which are composed of a single polypeptide chain.
Northern Blot: The northern blot is a technique used in molecular biology research to study gene expression by detection of RNA (or isolated mRNA) in a sample. Northern blotting involves the use of electrophoresis to separate RNA samples by size, and detection with a hybridization probe complementary to part of or the entire target sequence. The term ‘northern blot’ actually refers specifically to the capillary transfer of RNA from the electrophoresis gel to the blotting membrane. A general blotting procedure starts with extraction of total RNA from a sample or from cells. Eukaryotic mRNA can then be isolated through the use of oligo (dT) cellulose chromatography to isolate only those RNAs with a poly(A) tail. RNA samples are then separated by gel electrophoresis. Since the gels are fragile and the probes are unable to enter the matrix, the RNA samples, now separated by size, are transferred to a nylon membrane through a capillary or vacuum blotting system. A nylon membrane with a positive charge is the most effective for use in northern blotting since the negatively charged nucleic acids have a high affinity for them. The transfer buffer used for the blotting usually contains formamide because it lowers the annealing temperature of the probe-RNA interaction, thus eliminating the need for high temperatures, which could cause RNA degradation. Once the RNA has been transferred to the membrane, it is immobilized through covalent linkage to the membrane by UV light or heat. After a probe has been labeled, it is hybridized to the RNA on the membrane. The membrane is washed to ensure that the probe has bound specifically and to prevent background signals from arising. The hybrid signals are then detected by X-ray film and can be quantified by densitometry. The RNA samples are most commonly separated on agarose gels containing formaldehyde as a denaturing agent for the RNA to limit secondary structure. The gels can be stained with ethidium bromide (EtBr) and viewed under UV light to observe the quality and quantity of RNA before blotting. Polyacrylamide gel electrophoeresis with urea can also be used in RNA separation but it is most commonly used for fragmented RNA or microRNAs. Probes for northern blotting are composed of nucleic acids with a complementary sequence to all or part of the RNA of interest, they can be DNA, RNA, or oligonucleotides with a minimum of 25 complementary bases to the target sequence. RNA probes (riboprobes) that are transcribed in vitro are able to withstand more rigorous washing steps preventing some of the background noise. Commonly cDNA is created with labelled primers for the RNA sequence of interest to act as the probe in the northern blot. The probes must be labelled either with radioactive isotopes (32P) or with chemiluminescence in which alkaline phosphatase or horseradish peroxidase (HRP) break down chemiluminescent substrates producing a detectable emission of light. The chemiluminescent labelling can occur in two ways: either the probe is attached to the enzyme, or the probe is labelled with a ligand (e.g. biotin) for which the ligand (e.g., avidin or streptavidin) is attached to the enzyme (e.g. HRP). X-ray film can detect both the radioactive and chemiluminescent signals.
RNA Sequencing: RNA-seq (RNA sequencing), also called whole transcriptome shotgun sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample at a given moment in time. The high demand for low-cost sequencing has driven the development of high-throughput sequencing (or next-generation sequencing) technologies that parallelize the sequencing process, producing thousands or millions of sequences concurrently. In order to sequence RNA, the usual method is first to reverse transcribe the sample to generate cDNA fragments.
Reverse Transcriptase: A Reverse transcriptase (RT) is an enzyme used to generate complementary DNA (cDNA) from an RNA template, a process termed reverse transcription.
It is mainly associated with retroviruses. Retroviral RT has three sequential biochemical activities: RNA-dependent DNA polymerase activity, ribonuclease H, and DNA-dependent DNA polymerase activity.
Reverse Transcription: Reverse transcription is the process of generating a complementary DNA form an RNA template by a reverse transcriptase.
RT-PCR (Reverse transcription polymerase chain reaction): In RT-PCR, the RNA template is first converted into a complementary DNA (cDNA) using a reverse transcriptase. The cDNA is then used as a template for exponential amplification using PCR.
Quantitative Polymerase chain reaction (qPCR) or real-time polymerase chain reaction: A real-time polymerase chain reaction is a laboratory technique of molecular biology based on the polymerase chain reaction (PCR), which is used to amplify and simultaneously detect or quantify a targeted DNA molecule. The procedure follows the general principle of polymerase chain reaction (PCR); its key feature is that the amplified DNA is detected as the reaction progresses in “real time”. Two common methods for the detection of products in quantitative PCR are: (1) non-specific fluorescent dyes that intercalate with any double-stranded DNA, and (2) sequence-specific DNA probes consisting of oligonucleotides that are labelled with a fluorescent reporter, which permits detection only after hybridization of the probe with its complementary sequence to quantify nucleic acids. Quantitative PCR is carried out in a thermal cycler with the capacity to illuminate each sample with a beam of light of a specified wavelength and detect the fluorescence emitted by the excited fluorophore. The thermal cycler is also able to rapidly heat and chill samples, thereby taking advantage of the physicochemical properties of the nucleic acids and DNA polymerase. The PCR process generally consists of a series of temperature changes that are repeated 25-40 times. These cycles normally consist of three stages: the first, at around 95° C., allows the separation of the nucleic acid's double chain; the second, at a temperature of around 50-60° C., allows the binding of the primers with the DNA template; the third, at between 68-72° C., facilitates the polymerization carried out by the DNA polymerase. Due to the small size of the fragments the last step is usually omitted in this type of PCR as the enzyme is able to increase their number during the change between the alignment stage and the denaturing stage. In addition, some thermal cyclers add another short temperature phase lasting only a few seconds to each cycle, with a temperature of, for example, 80° C., in order to reduce the noise caused by the presence of primer dimers when a non-specific dye is used. The temperatures and the timings used for each cycle depend on a wide variety of parameters, such as: the enzyme used to synthesize the DNA, the concentration of divalent ions and deoxyribonucleotides (dNTPs) in the reaction and the bonding temperature of the primers. The type of quantitative PCR technique used depends on the DNA sequence in the samples, the technique can either use non-specific fluorochromes or hybridization probes.
The present invention relates to a method of diagnosing, monitoring a subject or determining the prognosis of a subject comprising the steps of (a) determining the expression level of at least one marker gene selected from the group consisting of the genes set out in table 1 in a sample of the subject to obtain a gene expression profile; (b) diagnosing, monitoring a subject or determining the prognosis of the subject based on the gene expression profile obtained in step (a).
In particular, the invention relates to a method of determining the prognosis of a patient comprising the steps of (a) determining the expression level of at least one marker gene selected from the group consisting of the marker genes set out in table 1 in a sample of the patient to obtain a gene expression profile; (b) determining the prognosis of the patient based on the gene expression profile obtained in step (a).
The patient may be a patient suffering from cancer or tumor. In preferred embodiments, the patient is a lung cancer patient. Most preferably the patient is a non-small cell lung cancer (NSCLC) patient.
Therefore, the invention in particular relates to a method of determining the prognosis of a cancer or tumor patient comprising the steps of (a) determining the expression level of at least one marker gene selected from the group consisting of the marker genes set out in table 1 in a sample of the cancer patient to obtain a gene expression profile; (b) determining the prognosis of the cancer patient based on the gene expression profile obtained in step (a).
In preferred embodiments, the invention relates to a method of determining the prognosis of a NSCLC patient comprising the steps of (a) determining the expression level of at least one marker gene selected from the group consisting of the marker genes set out in table 1 in a sample of the NSCLC cancer patient to obtain a gene expression profile; (b) determining the prognosis of the NSCLC cancer patient based on the gene expression profile obtained in step (a).
The expression level may be determined for at least one marker gene, at least 2 marker genes, at least 3 marker genes, at least 4 marker genes, at least 5 marker genes, at least 6 marker genes, at least 7 marker genes, at least 8 marker genes, at least 9 marker genes, at least 10 marker genes, at least 11 marker genes, at least 12 marker genes, at least 13 marker genes, at least 14 marker genes, at least 15 marker genes, at least 16 marker genes, at least 17 marker genes, at least 18 marker genes, at least 19 marker genes, at least 20 marker genes, at least 25 marker genes, at least 30 marker genes, at least 35 marker genes, at least 40 marker genes, at least 45 marker genes, at least 50 marker genes, at least 55 marker genes, at least 60 marker genes, at least 70 marker genes, at least 80 marker genes, at least 90 marker genes at least 100 marker genes.
The expression level may be determined for at least one marker gene, preferably at least 15 marker genes, more preferably at least 20 marker genes, even more preferably at least 30 marker genes, still more preferably at least 50 marker genes, most preferably at least 100 marker genes.
The expression level may be determined for example for one marker gene, 2 marker genes, 3 marker genes, 4 marker genes, 5 marker genes, 6 marker genes, 7 marker genes, 8 marker genes, 9 marker genes, 10 marker genes, 11 marker genes, 12 marker genes, 13 marker genes, 14 marker genes, 15 marker genes, 16 marker genes, 17 marker genes, 18 marker genes, 19 marker genes, 20 marker genes, 25 marker genes, 30 marker genes, 35 marker genes, 40 marker genes, 45 marker genes, 50 marker genes, 55 marker genes, 60 marker genes, 70 marker genes, 80 marker genes, 90 marker genes or 100 marker genes.
In specific embodiments, the at least one marker gene is selected from the group consisting of genes set out in table 2. In preferred embodiments, the at least one marker gene is selected from the group consisting of marker genes set out in table 3. In more preferred embodiments, the at least one marker gene is selected from group consisting of marker genes set out in table 4. In even more preferred embodiments, the at least one marker gene is selected from group consisting of marker genes set out in table 5.
In some embodiments at least 10 marker genes, such as 15, 25 or 25 marker genes, are selected from table 1. Preferably at least 30 marker genes, such as 35, 40 or 45 marker genes, more preferably at least 50 marker genes, such as 55, 60, 65, 70, 75, 80, 85, 90 or 95 marker genes, most preferably at least 100 marker genes are selected from table 1.
In some embodiments at least 10 marker genes, such as 15, 25 or 25 marker genes, are selected from table 2. Preferably at least 30 marker genes, such as 35, 40 or 45 marker genes, more preferably at least 50 marker genes, such as 55, 60, 65, 70, 75, 80, 85, 90 or 95 marker genes, most preferably at least 100 marker genes are selected from table 2.
In some embodiments at least 10 genes, such as 15, 25 or 25 marker genes, are selected from table 3. Preferably at least 30 marker genes, such as 35, 40 or 45 marker genes, more preferably at least 50 marker genes are selected from table 3.
In some embodiments at least 10 genes, such as 15 marker genes, are selected from table 4. Preferably at least 20 marker genes, such as 25 marker genes, more preferably at least 30 marker genes are selected from table 4.
In some embodiments at least 10 marker genes, such as 15 marker genes are selected from table 5.
The expression level of the at least one marker gene may be determined by any means known in the art. In a preferred embodiment of the present invention the determination of the expression level of the marker gene is accomplished by the measurement of nucleic acid. Thus, the expression level(s) may be determined by a method involving the detection of an mRNA encoded by the gene. Such methods include e.g. Nothem Blot analysis, (quantitative or semi-quantitative) RT-PCR, microarray analysis, and RNA sequencing (“next generation sequencing”).
For example, the measurement of the nucleic acid level of marker gene(s) expression may be assessed by purification of nucleic acid molecules (e.g. RNA) obtained from the sample, followed by hybridization with specific nucleic acid based probes selective for determining the expression level of the marker genes as defined herein. Comparison of expression levels may be accomplished visually or by means of an appropriate device. Methods for the detection of mRNA or expression products are known to the person skilled in the art.
Alternatively, the nucleic acid level of marker gene(s) expression may be detected in a microarray approach. Typically, sample nucleic acids derived from patients to be tested are processed and labeled, preferably with a fluorescent label. Subsequently, such nucleic acid molecules may be used in a hybridization approach with immobilized capture probes corresponding to the marker genes of the present invention. Suitable means for carrying out microarray analyses are known to the person skilled in the art. In a standard setup a microarray comprises immobilized high-density probes to detect a number of genes. The probes on the array are complementary to one or more parts of the mRNA sequence of the marker genes.
A microarray-based detection method typically comprises the following steps: (1) Isolating mRNA from a sample and optionally converting the mRNA to cDNA by reverse transcription, and subsequently labeling this RNA or cDNA. Methods for isolating RNA, converting it into cDNA by reverse transcription and for labeling nucleic acids are described in manuals for microarray technology. (2) Hybridizing the nucleic acids from step 1 with probes for the marker genes. The nucleic acids from a sample can be labeled with a dye, such as the fluorescent dyes Cy3 (red) or Cy5 (blue). Generally, a control sample is labeled with a different dye. (3) Detecting the hybridization of the nucleic acids from the sample with the probes and determining at least qualitatively, and more particularly quantitatively, the amounts of mRNA in the sample for marker genes investigated. The difference in the expression level between sample and control can be estimated based on a difference in the signal intensity. These can be measured and analyzed by appropriate software.
There is no limitation on the number of probes corresponding to the marker genes used, which are spotted on a microarray. Also, a marker gene can be represented by two or more probes, the probes hybridizing to different parts of a gene. Probes are designed for each selected marker gene. Such a probe is typically an oligonucleotide comprising 5-50 nucleotide residues. Longer DNAs can be synthesized by PCR or chemically. Methods for synthesizing such oligonucleotides and applying them on a substrate are well known in the field of microarrays. Genes other than the marker genes may be also spotted on the DNA array. For example, a probe for a gene whose expression level is not significantly altered may be spotted on the DNA array to normalize assay results or to compare assay results of multiple arrays or different assays. Such a gene is also termed herein as “reference gene”.
Alternatively, the nucleic acid level of marker gene(s) expression may be detected in a quantitative RT-PCR approach, preferably in a real-time PCR approach following the reverse transcription of the transcripts of interest. Typically, as first step, a transcript is reverse transcribed into a cDNA molecule according to any suitable method known to the person skilled in the art. A quantitative or real-time PCR approach may subsequently be carried out based on a first DNA strand obtained as described above.
Preferably, Taqman or Molecular Beacon probes as principal FRET-based probes of this type may be used for quantitative PCR detection. In both cases, the probes, serve as internal probes which are used in conjunction with a pair of opposing primers that flank the target region of interest, preferably a set of marker gene(s) specific oligonucleotides as defined herein above. Upon amplification of a target segment, the probe may selectively bind to the products at an identifying sequence in between the primer sites, thereby causing increases in FRET signaling relative to increases in target frequency.
Preferably, a Taqman probe to be used for a quantitative PCR approach according to the present invention may comprises a specific oligonucleotide as defined above of about 22 to 30 bases that is labeled on both ends with a FRET pair. Typically, the 5′ end will have a shorter wavelength fluorophore such as fluorescein (e.g. FAM) and the 3′ end is commonly labeled with a longer wavelength fluorescent quencher (e.g. TAMRA) or a non-fluorescent quencher compound (e.g. Black Hole Quencher). It is preferred that the probes to be used for quantitative PCR, in particular probes as defined herein above, have no guanine (G) at the 5′ end adjacent to the reporter dye in order to avoid quenching of the reporter fluorescence after the probe is degraded.
A Molecular Beacon probe to be used for a quantitative PCR approach according to the present invention preferably uses FRET interactions to detect and quantify a PCR product, with each probe having a 5′ fluorescent-labeled end and a 3′ quencher-labeled end. This hairpin or stem-loop configuration of the probe structure comprises preferably a stem with two short self-binding ends and a loop with a long internal target-specific region of about 20 to 30 bases.
Alternative detection mechanisms which may also be employed in the context of the present invention are directed to a probe fabricated with only a loop structure and without a short complementary stem region. An alternative FRET-based approach for quantitative PCR which may also be used in the context of the present invention is based on the use of two hybridization probes that bind to adjacent sites on the target wherein the first probe has a fluorescent donor label at the 3′ end and the second probe has a fluorescent acceptor label at its 5′ end.
Also detection techniques using molecular barcodes, for example color coded molecular barcodes (such as nCounter from Nanostring technologies) may be used. Typically, in such methods a reporter probe carrying the signal and a capture probe are used. After hybridization, the excess probes are removed and the complexes containing the target sequence hybridized to the signal probe and the capture probe are aligned, immobilized in a cartridge and the color codes of the signal probe are counted.
Alternatively, the nucleic acid level of marker gene(s) expression may be detected by RNA sequencing. RNA sequencing, also called whole transcriptome shotgun sequencing (WTSS), uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample at a given moment in time. Different methods used for next-generation sequencing are known in the art.
In specific embodiments the expression level is measured before administration and/or after administration of a least one dose of a therapeutic agent.
In preferred embodiments the gene expression profile of step (a) is obtained by determining the difference of the expression level of the at least one marker gene measured before administration of the therapeutic agent and after the administration of at least one dose of the therapeutic agent.
Therefore, some embodiments of the invention relate to a method of determining the prognosis of a patient comprising the steps of (a) determining the difference of the expression level of the at least one marker gene before administration of the therapeutic agent and after the administration of at least one dose of the therapeutic agent in sample of the patient to obtain a gene expression profile; (b) determining the prognosis of the patient based on the gene expression profile obtained in step (a).
In particular, some embodiments of the present invention relate to a method of determining the prognosis of a cancer patient, preferably a lung cancer patient, and most preferably a NSCLC patient, comprising the steps of (a) determining the difference of the expression level of the at least one marker gene before administration of the therapeutic agent and after the administration of at least one dose of the therapeutic agent in sample of the cancer patient to obtain a gene expression profile; (b) determining the prognosis of the cancer patient based on the gene expression profile obtained in step (a).
In this context therapeutic agents include all agents and therapies used for therapy or prevention of a disease, particularly of tumor or cancer diseases. Particularly preferred are surgery, radiation therapy, chemotherapy, chemoradiation, and/or treatment with kinase inhibitors, inhibitory and/or stimulatory checkpoint molecules (checkpoint modulators) or antibodies. Most preferably therapeutic agents are selected from vaccines and/or immunostimulatory compositions and/or immunotherapeutic agents, preferably as defined herein.
In one embodiment it is particularly preferred that the vaccine or immunostimulatory composition comprises at least one antigen, preferably a tumor antigen as defined herein.
A specific embodiment of the invention relates to a method of determining the prognosis of a cancer patient, preferably a lung cancer patient and more preferably a NSCLC patient comprising the steps of (a) determining the difference of the expression level of the at least one marker gene before administration of a vaccine or immunostimulatory composition comprising at least one tumor antigen of the group consisting of MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4 and after the administration of at least one dose of said vaccine or immunotherapeutic agent in a sample of the cancer patient to obtain a gene expression profile; (b) determining the prognosis of the cancer patient based on the gene expression profile obtained in step (a).
A specific embodiment of the invention relates to a method of determining the prognosis of a cancer patient, preferably a lung cancer patient and more preferably a NSCLC patient comprising the steps of (a) determining the difference of the expression level of the at least one marker gene before administration of a vaccine or immunostimulatory composition comprising the tumor antigens MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4 and after the administration of at least one dose of said vaccine or immunostimulatory composition in a sample of the cancer patient to obtain a gene expression profile; (b) determining the prognosis of the cancer patient based on the gene expression profile obtained in step (a).
Another specific embodiment of the invention relates to a method of determining the prognosis of a cancer patient, preferably a lung cancer patient, more preferably a NSCLC patient comprising the steps of (a) determining the difference of the expression level of the at least one marker gene before administration of a vaccine or immunostimulatory composition comprising the antigens MAGE-C1, MAGE-C2, NY-ESO-1, Survivin, 5T4, and Muc-1 and after the administration of at least one dose of said vaccine or immunotherapeutic agent in a sample of the NSCLC patient to obtain a gene expression profile; (b) determining the prognosis of the cancer patient based on the gene expression profile obtained in step (a).
The sample of the individual or patient can be any sample suitable for the analysis of the expression of the marker genes as disclosed herein. The sample of the individual or patient may be without limitation whole blood or fractions thereof, such as peripheral blood mono-nuclear cells (PBMCs). Preferably, the sample of the individual or patient comprises PBMCs. Alternatively, the sample may be any tissue of the patient, preferably tumor tissue.
In step (b) the prognosis of a cancer patient may be obtained based on the gene expression profile obtained in step (a). For example, the increase or decrease of the expression of the at least one marker gene may relate to a certain course or outcome of a diagnosed or detected disease. For example, the increase or decrease of the expression of the at least one marker gene may relate to a chance of survival or recovery from the disease, to an expected survival time of a subject. For example, the increase or decrease of the expression of the at least one marker gene as described herein may indicate the expected survival time of a subject. In particular, if the prognosis in step (b) is determined based on an expression profile of several genes, for example 30, 50 or 100 or more genes, algorithms can be used to determine the prognosis of a cancer patient. Preferably, clustering algorithms, more preferably hierarchical clustering algorithms can be used in step (b).
Typically, the therapeutic agent may be an immunostimulatory composition and/or a vaccine and/or an immunotherapeutic agent. The therapeutic agent may be a therapeutic protein as defined above or may comprise additionally a therapeutic protein. Preferably the therapeutic agent comprises the antigens MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4 or fragments thereof. The antigen(s) may be present as peptides or proteins and/or are encoded by at least one nucleotide sequence. Preferably the antigens are encoded by at least one mRNA molecule. In a specific embodiment the therapeutic agent is at least one mRNA molecule encoding the antigens MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4 or fragments thereof.
In the context of this invention “MAGE-C1” is the melanoma antigen family C, 1 and the preferred sequence of the RNA, preferably of the mRNA, encoding “MAGE-C1”—if being used in the immunostimulatory composition—is shown in SEQ ID NO: 1, more preferably in SEQ ID NO: 2, and even more preferably in SEQ ID NO: 3.
In the context of this invention “MAGE-C2” is the melanoma antigen family C2 and the preferred sequence of the RNA, preferably of the mRNA, encoding “MAGE-C2”—if being used in the immunostimulatory composition—is shown in SEQ ID NO: 4, and even more preferably SEQ ID NO: 5.
In the context of this invention “NY-ESO-1” is cancer/testis antigen 1B and the preferred sequence of the RNA, preferably of the mRNA, encoding “NY-ESO-1”—if being used in the immunostimulatory composition—is shown in SEQ ID NO: 6, and in SEQ ID NO: 7.
In the context of this invention “Survivin” is baculoviral IAP repeat-containing 5 (survivin) and the preferred sequence of the RNA, preferably of the mRNA, encoding “survivin”—if being used in the immunostimulatory composition—is shown in SEQ ID NO: 8, and even more preferably in SEQ ID NO: 9.
In the context of this invention “5T4” is trophoblast glycoprotein and the preferred sequence of the RNA, preferably of the mRNA, encoding “5T4”—if being used in the vaccine—is shown in SEQ ID NO: 10, and even more preferably in SEQ ID NO: 11.
The immunostimulatory composition may comprise antigens, antigenic proteins or antigenic peptides or nucleic acids such as DNA or RNA encoding antigens, antigenic proteins or antigenic peptides capable to effectively stimulate the (adaptive) immune system to allow treatment of cancer, preferably lung cancer, especially of non-small cell lung cancer (NSCLC). Preferably the immunostimulatory composition comprises at least one RNA encoding at least one antigen, antigenic protein or antigenic peptide.
Preferably, the immunostimulatory composition or vaccine comprises at least one RNA encoding at least one antigen selected from the group consisting of MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4, wherein the at least one RNA is complexed to a complexing agent, preferably protamine.
The vaccine may contain the active immunostimulatory composition. The vaccine may additionally contain a pharmaceutically acceptable carrier and/or further auxiliary substances and additives and/or adjuvants. According to a particularly preferred embodiment, the antigens are selected from the group consisting of MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4.
According to another embodiment, the antigens are selected from the group consisting of
The antigens are described in detail in WO2015024664, which is incorporated herein by reference. Also the multi-antigenic CV9104 is an mRNA-based immunotherapeutic which encodes for the six antigens Muc-1, PSA, PSCA, PSMA, STEAP-1 and PAP is described in detail in WO2015024664.
In a preferred embodiment, the vaccine comprises a safe and effective amount of antigen encoding RNA of the immunostimulatory composition as defined above. As used herein, “safe and effective amount” means an amount of the RNA of the immunostimulatory composition in the vaccine as defined above, that is sufficient to significantly induce a positive modification of the disease, preferably cancer, more preferably lung cancer, even more preferably of a non-small-cell lung cancer (NSCLC) related condition to be treated, more preferably of conditions related to the three main sub-types of non-small-cell lung cancer (NSCLC) including, without being restricted thereto, squamous cell lung carcinoma, adenocarcinoma and large cell lung carcinoma. At the same time, however, a “safe and effective amount” is small enough to avoid serious side-effects, that is to say to permit a sensible relationship between advantage and risk. The determination of these limits typically lies within the scope of sensible medical judgment. In relation to the vaccine, the expression “safe and effective amount” preferably means an amount of the RNA that is suitable for stimulating the adaptive immune system in such a manner that no excessive or damaging immune reactions are achieved but, preferably, also no such immune reactions below a measurable level. Such a “safe and effective amount” of the at least one RNA of the immunostimulatory composition in the vaccine as defined above may furthermore be selected in dependence of the type of RNA, e.g. monocistronic, bi- or even multicistronic RNA, since a bi- or even multicistronic RNA may lead to a significantly higher expression of the encoded antigen(s) than use of an equal amount of a monocistronic RNA. A “safe and effective amount” of the at least one RNA of the immunostimulatory composition as defined above, which is contained in the vaccine, will furthermore vary in connection with the particular condition to be treated and also with the age and physical condition of the patient to be treated, the severity of the condition, the duration of the treatment, the nature of the accompanying therapy, of the particular pharmaceutically acceptable carrier used, and similar factors, within the knowledge and experience of the accompanying doctor.
The vaccine typically contains a pharmaceutically acceptable carrier. The expression “pharmaceutically acceptable carrier” as used herein preferably includes the liquid or non-liquid basis of the vaccine. If the vaccine is provided in liquid form, the carrier will typically be pyrogen-free water; isotonic saline or buffered (aqueous) solutions, e.g. phosphate-, citrate-buffered solutions, etc.
The vaccine can additionally contain one or more auxiliary substances in order to further increase the immunogenicity. A synergistic action of the at least one RNA of the active (immunostimulatory) composition as defined above and of an auxiliary substance, which may be optionally also contained in the vaccine as described above, is preferably achieved thereby. Depending on the various types of auxiliary substances, various mechanisms can come into consideration in this respect. For example, compounds that permit the maturation of dendritic cells (DCs), for example lipopolysaccharides, TNF-alpha or CD40 ligand, form a first class of suitable auxiliary substances. In general, it is possible to use as auxiliary substance any agent that influences the immune system in the manner of a “danger signal” (LPS, GP96, etc.) or cytokines, such as GM-CSF, which allow an immune response produced by the immune-stimulating adjuvant according to the invention to be enhanced and/or influenced in a targeted manner. Particularly preferred auxiliary substances are cytokines, such as monokines, lymphokines, interleukins or chemokines, that—additional to induction of the adaptive immune response by the encoded at least two antigens—promote the innate immune response, such as IL-1, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12, IL-13, IL-14, IL-15, IL-16, IL-17, IL-18, IL-19, IL-20, IL-21, IL-22, IL-23, IL-24, IL-25, IL-26, IL-27, IL-28, IL-29, IL-30, IL-31, IL-32, IL-33, INF-alpha, IFN-beta, INF-gamma, GM-CSF, G-CSF, M-CSF, LT-beta or TNF-alpha, growth factors, such as hGH.
Further additives which may be included in the vaccine are emulsifiers, such as, for example, Tween®; wetting agents, such as, for example, sodium lauryl sulfate; colouring agents; taste-imparting agents, pharmaceutical carriers; tablet-forming agents; stabilizers; antioxidants; preservatives. The vaccine can also additionally contain any further compound, which is known to be immune-stimulating due to its binding affinity (as ligands) to human Toll-like receptors or due to its binding affinity (as ligands) to murine Toll-like receptors. Another class of compounds, which may be added to the vaccine, may be CpG nucleic acids, in particular CpG-RNA or CpG-DNA. A CpG-RNA or CpG-DNA can be a single-stranded CpG-DNA (ss CpG-DNA), a double-stranded CpG-DNA (dsDNA), a single-stranded CpG-RNA (ss CpG-RNA) or a double-stranded CpG-RNA (ds CpG-RNA).
Moreover, the invention relates to a method of determining whether a cancer patient responds to a therapeutic agent comprising the steps of
Another aspect of the invention refers to a kit, diagnostic composition or device for the analysis of the expression of at least one marker gene as described herein. In one embodiment, the invention refers to a kit, diagnostic composition or device for the analysis of the expression of at least one marker gene of table 1 comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene of table 1. Some embodiments relate to a kit, diagnostic composition or device comprising at least 10 primers and/or probes, preferably at least 30 primers and/or probes, more preferably at least 50 primers and/or probes, most preferably at least 100 primers and/or probes selective for determining the expression level of at least 10, 30, 50 or 100 marker genes of table 1. A further embodiment refers to a kit, diagnostic composition or device for the analysis of the expression of at least one marker gene of table 2 comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene of table 2. Some embodiments relate to a kit, diagnostic composition or device comprising at least 10 primers and/or probes, preferably at least 30 primers and/or probes, more preferably at least 50 primers and/or probes, most preferably at least 100 primers and/or probes selective for determining the expression level of at least 10, 30, 50 or 100 marker genes of table 2. In a further embodiment, the invention refers to a kit, diagnostic composition or device for the analysis of the expression of at least one marker gene of table 3 comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene of table 3. Further embodiments relate to a kit, diagnostic composition or device comprising at least 10 primers and/or probes, preferably at least 30 primers and/or probes, more preferably at least 40 primers and/or probes, most preferably at least 50 primers and/or probes selective for determining the expression level of at least 10, 30, 40 or 50 marker genes of table 3. In another embodiment, the invention refers to a kit, diagnostic composition or device for the analysis of the expression of at least one marker gene of table 4 comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene of table 4. Further embodiments relate to a kit, diagnostic composition or device comprising at least 10 primers and/or probes, preferably at least 20 primers and/or probes, more preferably at least 25 primers and/or probes, most preferably at least 30 primers and/or probes selective for determining the expression level of at least 10, 20, 25 or 30 marker genes of table 4. In another embodiment, the invention refers to a kit, diagnostic composition or device for the analysis of the expression of at least one marker gene, preferably at least 5 marker genes, more preferably at least 10 marker genes of table 5 comprising at least one primer and/or probe, preferably at least 5 primers and/or probes, more preferably at least 10 primers and/or probes selective for determining the expression level of at least one marker gene of table 5.
A further embodiment refers to a kit, diagnostic composition or device for the analysis of the expression of at least one marker gene of table 2B comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene of table 2B. Some embodiments relate to a kit, diagnostic composition or device comprising at least 10 primers and/or probes, preferably at least 30 primers and/or probes, more preferably at least 50 primers and/or probes, most preferably at least 90 primers and/or probes selective for determining the expression level of at least 10, 30, 50 or 90 marker genes of table 2B. In a further embodiment, the invention refers to a kit, diagnostic composition or device for the analysis of the expression of at least one marker gene of table 3B comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene of table 3B. Further embodiments relate to a kit, diagnostic composition or device comprising at least 10 primers and/or probes, preferably at least 30 primers and/or probes, more preferably at least 40 primers and/or probes, most preferably at least 40 primers and/or probes selective for determining the expression level of at least 10, 30 or 40 marker genes of table 3B. In another embodiment, the invention refers to a kit, diagnostic composition or device for the analysis of the expression of at least one marker gene of table 4B comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene of table 4B. Further embodiments relate to a kit, diagnostic composition or device comprising at least 10 primers and/or probes, preferably at least 20 primers and/or probes, more preferably at least 25 primers and/or probes selective for determining the expression level of at least 10, 20 or 25 marker genes of table 4B. In another embodiment, the invention refers to a kit, diagnostic composition or device for the analysis of the expression at least one marker gene, preferably at least 5 marker genes, more preferably at least 8 marker genes of table 5 comprising at least one primer and/or probe, preferably at least 5 primers and/or probes, more preferably at least 8 primers and/or probes selective for determining the expression level of at least of at least 5 or 8 marker genes of table 5B.
The kit as described herein may further comprise an enzyme for primer elongation, nucleotides and/or labeling agents.
Another aspect of the invention refers to a microarray for the analysis of the expression of at least one marker gene as described herein. In one embodiment, the invention refers to a microarray for the analysis of the expression of at least one marker gene of table 1 comprising at least one probe selective for determining the expression level of at least one marker gene of table 1. Some embodiments relate to a microarray comprising at least 10 probes, preferably at least 30 probes, more preferably at least 50 probes, most preferably at least 100 probes selective for determining the expression level of at least 10, 30, 50 or 100 marker genes of table 1. A further embodiment refers to a microarray for the analysis of the expression of at least one marker gene of table 2 comprising at least one probe selective for determining the expression level of at least one marker gene of table 2. Some embodiments relate to a microarray comprising at least 10 probes, preferably at least 30 probes, more preferably at least 50 probes, most preferably at least 100 probes selective for determining the expression level of at least 10, 30, 50 or 100 marker genes of table 2. In a further embodiment, the invention refers to a microarray for the analysis of the expression of at least one marker gene of table 3 comprising at least one probe selective for determining the expression level of at least one marker gene of table 3. Further embodiments relate to a microarray comprising at least 10 probes, preferably at least 30 probes, more preferably at least 40 probes, most preferably at least 50 probes selective for determining the expression level of at least 10, 30, 40 or 50 marker genes of table 3. In another embodiment, the invention refers to a microarray for the analysis of the expression of at least one marker gene of table 4 comprising at least one probe selective for determining the expression level of at least one marker gene of table 4. Further embodiments relate to a microarray comprising at least 10 probes, preferably at least 20 probes, more preferably at least 25 probes, most preferably at least 30 probes selective for determining the expression level of at least 10, 20, 25 or 30 marker genes of table 4. In another embodiment, the invention refers to a microarray for the analysis of the expression of at least one marker gene, preferably at least 5 marker genes, more preferably at least 10 marker genes of table 5 comprising at least one probe, preferably at least 5 probes, more preferably at least 10 probes selective for determining the expression level of at least one marker gene of table 5.
A further embodiment refers to a microarray for the analysis of the expression of at least one marker gene of table 2B comprising at least one probe selective for determining the expression level of at least one marker gene of table 2B. Some embodiments relate to a microarray comprising at least 10 probes, preferably at least 30 probes, more preferably at least 50 probes, most preferably at least 90 probes selective for determining the expression level of at least 10, 30, 50 or 90 marker genes of table 2B. In a further embodiment, the invention refers to a microarray for the analysis of the expression of at least one marker gene of table 3B comprising at least one probe selective for determining the expression level of at least one marker gene of table 3B. Further embodiments relate to a microarray comprising at least 10 probes, preferably at least 30 probes, more preferably at least 40 probes selective for determining the expression level of at least 10, 30 or 40 marker genes of table 3B. In another embodiment, the invention refers to a microarray for the analysis of the expression of at least one marker gene of table 4B comprising at least one probe selective for determining the expression level of at least one marker gene of table 4B. Further embodiments relate to a microarray comprising at least 10 probes, preferably at least 20 probes, more preferably at least 25 probes selective for determining the expression level of at least 10, 20 or 25 marker genes of table 4B. In another embodiment, the invention refers to a microarray for the analysis of the expression of at least one marker gene, preferably at least 5 marker genes, more preferably at least 8 marker genes of table 5B comprising at least one probe, preferably at least 5 probes, more preferably at least 8 probes selective for determining the expression level of at least one marker gene of table 5B.
Another aspect of the invention refers to the use of a microarray as described herein for determining the prognosis of a cancer patient, preferably a lung cancer patient and more preferably a NSCLC patient. A further aspect of the invention refers to the use of a kit as described herein for determining the prognosis of a cancer patient, preferably a lung cancer patient and more preferably a NSCLC patient.
Another aspect refers to a non-transitory computer readable storage medium with an executable program stored thereon, wherein the program is for diagnosing, monitoring a subject, preferably a lung cancer patient and more preferably a NSCLC patient or determining the prognosis of a subject, preferably a lung cancer patient and more preferably a NSCLC patient and wherein the program instructs a microprocessor to perform one or more of the steps of any of the methods described herein.
The Examples shown in the following are merely illustrative and shall describe the present invention in a further way. These Examples shall not be construed to limit the present invention thereto.
CV9201 as described in WO2009046974 and Sebastian et al. BMC Cancer 2014, 14:748) is an mRNA-based cancer immunotherapeutic agent/vaccine comprising following cancer antigens: MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4. Repeated vaccinations of NSCLC patients with 320 μg RNA for each antigen (1.600 μg RNA in total) were carried out at weeks 1, 2, 3, 5, and 7. Peripheral blood samples were taken at weeks 0 (baseline), 5 and 9 (2 weeks post 3rd treatment and 2 weeks post 5th treatment, respectively).
Peripheral blood mono-nuclear cells (PBMCs) were isolated by Ficoll density centrifugation. Briefly, around 20 ml of blood were pipetted layered onto a LeucoSep tube (greiner bio-one) and centrifuged for 20 minutes without brake. PBMCs from the interphase were washed three times in PBS and suspended in cryo SFM (PromoCell) and cryopreserved in liquid nitrogen. Cells were thawed for immune analyses and 1 million left-over PBMCs were suspended in PBS and frozen.
RNA was isolated from re-thawed PBMCs using RNEasy (Qiagen) according to the manufacturer's instructions. RNA quality control was performed on a 2100 Bioanalyzer (Agilent Technologies) and a RIN threshold of 6.5 was used as cutoff. Cyanine-3-labelling of cRNA and hybridization using the Agilent SurePrint G3 Human Gene Expression 8×60K v2 Microarray platform was performed by IMGM according to manufacturer's manuals (Agilent Technologies). Raw data was processed using following software tools: Feature Extraction 10.7.3.1 and GeneSpring GX 12.6.1. Quantile normalization was performed and log 2-transformed and filtered for probes detectable in at least one sample.
Altogether 22 stage IV non-small cell lung cancer patients were evaluable in the transcriptional profiling study and gene expression data was obtained for 48,605 probes. To reduce the data set, we made use of blood transcriptional modules (BTMs) developed by the Pulendran group [1]. These altogether 346 BTMs represent sets of genes, which are transcriptionally co-regulated. Most of these BTMs reflect an immunological process, such as signaling pathways or represent sets of genes specifically enriched in immune cells, such as T or B cells. We first calculated the BTM activity scores, which represent the mean expression of all genes contained in a module. Probes with the highest average expression across all samples were chosen for genes targeted by multiple probes.
To monitor changes between baseline and post vaccine time points, BTM activity score differences between week 0 (pre-treatment time point) and week 5 (2 weeks post 3rd treatment) were calculated (Table 6). More specifically, gene expression differences between week 5 and week 0 were calculated for each patient in cluster 1. Subsequently, the mean of the week 5 to 0 differences was determined for all patients in cluster 1 (Week5_0 GE difference_mean_pat_clust1). Analogously, gene expression differences between week 5 and week 0 were calculated for each patient in cluster 2. Subsequently, the mean of the week 5 to 0 differences was determined for all patients in cluster 2 (Week5_0 GE difference_mean_pat_clust2). Both values (“Week5_0 GE difference_mean_pat_clust1” and “Week5_0 GE difference_mean_pat_clust2”) thus signify the mean change in gene expression comparing post treatment week 5 with the baseline value week 0 within a given group of patients. The difference between “Week5_0 GE difference_mean_pat_clust1” and “Week5_0 GE difference_mean_pat_clust2” was calculated (difference).
Unsupervised hierarchical clustering of module activity scores identified three distinct clusters of BTM week 5 to week 0 changes: a T/NK cell cluster, a cell cycle cluster and a myeloid/immune activation cluster (
We next sought to determine the single genes either driving or being associated with the clustering of the BTMs. To this end, gene expression differences between week 5 and corresponding week 0 samples were calculated for the entire transcriptome. As described above, probes with highest average expression were chosen if genes were targeted by multiple probes.
To identify genes differentially expressed in patient cluster 1 compared to cluster 2, following approaches were utilized: patients were grouped according to aforementioned clusters Genes were ranked according to p values comparing patient clusters 1 and 2 (t test) or clusters 1 versus 2a and 2b (ANOVA). Thus, altogether four comparisons were performed. The first top 100 hits were picked from each comparison. In addition, gene set enrichment analysis was performed to identify the top 15 BTMs enriched at week 5 in the patient clusters 1, 2a and 2b. Leading edge genes for these top 15 BTMs were identified and all duplicate genes were removed. Thus, a final list was generated comprising 914 single genes (as shown in Table 1). By unsupervised hierarchical clustering of these single gene expression changes (914 genes) (week 5 to week 0 differences) the patients could be segregated into the two groups of short term survivors and moderate/longterm survivors. Unsupervised hierarchical clustering of BTM activity scores was performed using Euclidean distance and average linkage clustering. The 915 genes were ranked based on their ability to differentiate between patients derived from cluster 1 and patients derived from cluster 2. Top 100 (Table 2;
The multi-antigenic CV9104 as described in WO2015024664 is an mRNA-based immunotherapeutic and a further development of CV9103 (Kübler H, et al. “Self-adjuvanted mRNA vaccination in advanced prostate cancer patients: a first-in-man phase I/IIa study.” J Immunother Cancer. 2015 Jun. 16; 3:26.). It encodes for six cancer antigens associated with prostate cancer: Muc-1, PSA, PSCA, PSMA, STEAP-1 and PAP. A total of 46 pre-operative prostate cancer patients were divided into three groups. Cohort A received up to four intradermal immunizations of 160 μg RNA for each antigen using the needle-free injection device Tropis. Patients in cohort B received 320 μg of RNA for each antigen by intradermal syringe-needle injection whereas cohort C patient remained untreated. Venous blood samples for gene expression profiling were taken at week 6 (1-2 weeks after the fourth mRNA treatment) and 8 weeks after prostatectomy. Blood was harvested into PAXgene® RNA tubes, frozen and stored at −80° C. until further processing. 14 subjects in cohort A, and 16 subjects each in cohorts B and C were evaluable.
Frozen PAXgene® samples were transferred to IMGM for isolation of RNA and microarray analysis. Blood samples were thawed and incubated at room temperature to ensure complete lysis of leukocytes before RNA isolation. Total RNA including miRNAs were isolated using the PAXgene® Blood miRNA Kit (Qiagen) according to the manufacturer's instructions including on-column DNAse digestion. Total RNA was eluted in 80 μl buffer.
RNA quantity and quality were assessed using the NanoDrop NK-1000 spectral photometer (peqlab) and integrity was analyzed on the 2100 Bioanalyzer using RNA 6000 Nano LabChip Kits (Agilent Technologies). Cyanine-3-labelling of cRNA and hybridization using the Agilent SurePrint G3 Human Gene Expression 8×60K v2 Microarray platform was performed by IMGM according to manufacturer's manuals (Agilent Technologies). Raw data was processed using following software tools: Feature Extraction 10.7.3.1 and GeneSpring GX 13.1.1 (both Agilent Techlogies). Quantile normalization was applied to the data set and log 2-transformed and filtered for probes detectable in at least one sample.
To determine the transcriptional changes in prostate cancer patients after CV9104 treatment we performed gene set enrichment analysis (GSEA) using blood transcriptional modules (BTMs) as gene sets (Li S et al. “Molecular signatures of antibody responses derived from a systems biology study of five human vaccines” Nat Immunol. 2014 February; 15(2):195-204). Gene lists were ranked based on paired t-test P values comparing the week 6 with baseline samples for each of the three patient cohorts. In addition, we also combined arms A and B (treated cohorts) to increase the statistical power and sensitivity of the GSEA approach. The GSEA results show that modules consistent with a T and NK cell profile were up-regulated at week 6 in subjects receiving CV9104 treatment but not in the control arm C (
Gene Set Enrichment Analyses were performed comparing week 6 to week 1, and week 8 to week 1, for each of the two vaccine arms, and the control arm, individually, using the Blood Transcriptome Module gene sets as probes.
For each contrast, the 10 Blood Transcriptome Modules having the highest enrichment scores were selected, and the leading edge genes (the subset of genes that contribute most to the enrichment score) from each module were selected.
For this combined list of 725 unique leading edge genes, mean expression values for each experimental arm and time point were calculated. For transcripts that were represented by more than one probe in the microarray, the probe expression values of the probe having the highest mean expression in all samples was used.
Log 2 fold changes (differences in log 2 expression values) between week 6 and week 1, for each vaccine arm and the control arm were calculated.
To identify the genes that are regulated from week 1 to week 6 most differently in the vaccine recipients and the control group, the difference between the combined vaccine arm log 2 fold changes and the control arm log 2 fold changes was calculated (table 17). In table 17 the genes based on the absolute value of this difference, such that the genes at the top of the list are the most differently regulated between vaccine recipients and the control arm, whether those genes are up regulated to a greater extent over time, in vaccine recipients than in the control group, or down regulated to a greater extent over time, in vaccine recipients than in the control group.
Subsequently a subset of 402 of the 725 prostate cancer vaccine leading edge genes was selected, that were also found in the nsclc set of select genes (table 18).
This subset of select genes identified from analyses of both nsclc and prostate vaccine trials was ranked in the identical way as the total list of prostate vaccine leading edge genes, such that in table 18 the genes at the top of the list are the most differently regulated between prostate cancer vaccine recipients and the control arm, whether those genes are up regulated to a greater extent over time, in vaccine recipients than in the control group, or down regulated to a greater extent over time, in vaccine recipients than in the control group.
The invention further comprises the following embodiments:
A method of determining the prognosis of a patient comprising the steps of
Method according to embodiment 1, wherein the patient is a cancer or tumor patient.
Method according to embodiment 1 or 2, wherein the at least one marker gene is selected from the group consisting of marker genes set out in table 2.
Method according to embodiment 3, wherein the at least one marker gene is selected from the group consisting of marker genes set out in table 3.
Method according to embodiment 4, wherein the at least one marker gene is selected from group consisting of marker genes set out in table 4.
Method according to embodiment 5, wherein the at least one marker gene is selected from group consisting of marker genes set out in table 5.
Method according to embodiment 1, wherein at least 10 marker genes, preferably at least 30 marker genes, more preferably at least 50 marker genes, most preferably at least 100 marker genes are selected from table 1.
Method according to embodiment 3, wherein at least 10 marker genes, preferably at least 30 marker genes, more preferably at least 50 marker genes, most preferably at least 100 marker genes are selected from table 2.
Method according to embodiment 4, wherein at least 10 marker genes, preferably at least 30 marker genes, more preferably at least 50 marker genes are selected from table 3.
Method according embodiment 5, wherein at least 10 marker genes, preferably at least 20 marker genes, more preferably at least 30 marker genes a selected from the group consisting of from table 4.
Method according to any one of the preceding embodiments, wherein the expression level of at least one marker gene is measured before administration and/or after administration of at least one dose of a therapeutic agent.
Method according to embodiment 11, wherein the gene expression profile of step (a) is obtained by determining the difference of the expression level of the at least one marker gene measured before administration of the therapeutic agent and after administration of at least one dose of the therapeutic agent.
Method according to embodiment 11 or 12, wherein the therapeutic agent is an immunostimulatory composition and/or a vaccine and/or an immunotherapeutic agent.
Method according to any one of embodiments 11 to 13, wherein the immunostimulatory composition and/or vaccine comprises at least one antigen selected from the group consisting of MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4 or fragments or variants thereof.
Method according to any one of embodiments 11 to 14, wherein the immunostimulatory composition and/or vaccine comprises the antigens MAGE-C1, MAGE-C2, NY-ESO-1, Survivin and 5T4 or fragments or variants thereof.
Method according to embodiment 11 to 15, wherein the antigen(s) are present as peptides or proteins and/or are encoded by at least one nucleotide sequence.
Method according to any one of embodiments 11 to 16, wherein the antigen(s) are encoded by at least one mRNA molecule.
Method according to any one of embodiments 11 to 17, wherein the cancer is selected from the group consisting of Acute Lymphoblastic Leukemia, Adult; Acute Lymphoblastic Leukemia, Childhood; Acute Myeloid Leukemia, Adult; Adrenocortical Carcinoma; Adrenocortical Carcinoma, Childhood; AIDS-Related Lymphoma; AIDS-Related Malignancies; Anal Cancer; Astrocytoma, Childhood Cerebellar; Astrocytoma, Childhood Cerebral; Bile Duct Cancer, Extrahepatic; Bladder Cancer; Bladder Cancer, Childhood; Bone Cancer, Osteosarcoma/Malignant Fibrous Histiocytoma; Brain Stem Glioma, Childhood; Brain Tumor, Adult; Brain Tumor, Brain Stem Glioma, Childhood; Brain Tumor, Cerebellar Astrocytoma, Childhood; Brain Tumor, Cerebral Astrocytoma/Malignant Glioma, Childhood; Brain Tumor, Ependymoma, Childhood; Brain Tumor, Medulloblastoma, Childhood; Brain Tumor, Supratentorial Primitive Neuroectodermal Tumors, Childhood; Brain Tumor, Visual Pathway and Hypothalamic Glioma, Childhood; Brain Tumor, Childhood (Other); Breast Cancer; Breast Cancer and Pregnancy; Breast Cancer, Childhood; Breast Cancer, Male; Bronchial Adenomas/Carcinoids, Childhood: Carcinoid Tumor, Childhood; Carcinoid Tumor, Gastrointestinal; Carcinoma, Adrenocortical; Carcinoma, Islet Cell; Carcinoma of Unknown Primary; Central Nervous System Lymphoma, Primary; Cerebellar Astrocytoma, Childhood; Cerebral Astrocytoma/Malignant Glioma, Childhood; Cervical Cancer; Childhood Cancers; Chronic Lymphocytic Leukemia; Chronic Myelogenous Leukemia; Chronic Myeloproliferative Disorders; Clear Cell Sarcoma of Tendon Sheaths; Colon Cancer; Colorectal Cancer, Childhood; Cutaneous T-Cell Lymphoma; Endometrial Cancer; Ependymoma, Childhood; Epithelial Cancer, Ovarian; Esophageal Cancer; Esophageal Cancer, Childhood; Ewing's Family of Tumors; Extracranial Germ Cell Tumor, Childhood; Extragonadal Germ Cell Tumor; Extrahepatic Bile Duct Cancer; Eye Cancer, Intraocular Melanoma; Eye Cancer, Retinoblastoma; Gallbladder Cancer; Gastric (Stomach) Cancer; Gastric (Stomach) Cancer, Childhood; Gastrointestinal Carcinoid Tumor; Germ Cell Tumor, Extracranial, Childhood; Germ Cell Tumor, Extragonadal; Germ Cell Tumor, Ovarian; Gestational Trophoblastic Tumor; Glioma. Childhood Brain Stem; Glioma. Childhood Visual Pathway and Hypothalamic; Hairy Cell Leukemia; Head and Neck Cancer; Hepatocellular (Liver) Cancer, Adult (Primary); Hepatocellular (Liver) Cancer, Childhood (Primary); Hodgkin's Lymphoma, Adult; Hodgkin's Lymphoma, Childhood; Hodgkin's Lymphoma During Pregnancy; Hypopharyngeal Cancer; Hypothalamic and Visual Pathway Glioma, Childhood; Intraocular Melanoma; Islet Cell Carcinoma (Endocrine Pancreas); Kaposi's Sarcoma; Kidney Cancer; Laryngeal Cancer; Laryngeal Cancer, Childhood; Leukemia, Acute Lymphoblastic, Adult; Leukemia, Acute Lymphoblastic, Childhood; Leukemia, Acute Myeloid, Adult; Leukemia, Acute Myeloid, Childhood; Leukemia, Chronic Lymphocytic; Leukemia, Chronic Myelogenous; Leukemia, Hairy Cell; Lip and Oral Cavity Cancer; Liver Cancer, Adult (Primary); Liver Cancer, Childhood (Primary); Lung Cancer, Non-Small Cell; Lung Cancer, Small Cell; Lymphoblastic Leukemia, Adult Acute; Lymphoblastic Leukemia, Childhood Acute; Lymphocytic Leukemia, Chronic; Lymphoma, AIDS-Related; Lymphoma, Central Nervous System (Primary); Lymphoma, Cutaneous T-Cell; Lymphoma, Hodgkin's, Adult; Lymphoma, Hodgkin's; Childhood; Lymphoma, Hodgkin's During Pregnancy; Lymphoma, Non-Hodgkin's, Adult; Lymphoma, Non-Hodgkin's, Childhood; Lymphoma, Non-Hodgkin's During Pregnancy; Lymphoma, Primary Central Nervous System; Macroglobulinemia, Waldenstrom's; Male Breast Cancer; Malignant Mesothelioma, Adult; Malignant Mesothelioma, Childhood; Malignant Thymoma; Medulloblastoma, Childhood; Melanoma; Melanoma, Intraocular; Merkel Cell Carcinoma; Mesothelioma, Malignant; Metastatic Squamous Neck Cancer with Occult Primary; Multiple Endocrine Neoplasia Syndrome, Childhood; Multiple Myeloma/Plasma Cell Neoplasm; Mycosis Fungoides; Myelodysplasia Syndromes; Myelogenous Leukemia, Chronic; Myeloid Leukemia, Childhood Acute; Myeloma, Multiple; Myeloproliferative Disorders, Chronic; Nasal Cavity and Paranasal Sinus Cancer; Nasopharyngeal Cancer; Nasopharyngeal Cancer, Childhood; Neuroblastoma; Neurofibroma; Non-Hodgkin's Lymphoma, Adult; Non-Hodgkin's Lymphoma, Childhood; Non-Hodgkin's Lymphoma During Pregnancy; Non-Small Cell Lung Cancer; Oral Cancer, Childhood; Oral Cavity and Lip Cancer; Oropharyngeal Cancer; Osteosarcoma/Malignant Fibrous Histiocytoma of Bone; Ovarian Cancer, Childhood; Ovarian Epithelial Cancer; Ovarian Germ Cell Tumor; Ovarian Low Malignant Potential Tumor; Pancreatic Cancer; Pancreatic Cancer, Childhood′, Pancreatic Cancer, Islet Cell; Paranasal Sinus and Nasal Cavity Cancer; Parathyroid Cancer; Penile Cancer; Pheochromocytoma; Pineal and Supratentorial Primitive Neuroectodermal Tumors, Childhood; Pituitary Tumor; Plasma Cell Neoplasm/Multiple Myeloma; Pleuropulmonary Blastoma; Pregnancy and Breast Cancer; Pregnancy and Hodgkin's Lymphoma; Pregnancy and Non-Hodgkin's Lymphoma; Primary Central Nervous System Lymphoma; Primary Liver Cancer, Adult; Primary Liver Cancer, Childhood; Prostate Cancer; Rectal Cancer; Renal Cell (Kidney) Cancer; Renal Cell Cancer, Childhood; Renal Pelvis and Ureter, Transitional Cell Cancer; Retinoblastoma; Rhabdomyosarcoma, Childhood; Salivary Gland Cancer; Salivary Gland′ Cancer, Childhood; Sarcoma, Ewing's Family of Tumors; Sarcoma, Kaposi's; Sarcoma (Osteosarcoma)/Malignant Fibrous Histiocytoma of Bone; Sarcoma, Rhabdomyosarcoma, Childhood; Sarcoma, Soft Tissue, Adult; Sarcoma, Soft Tissue, Childhood; Sezary Syndrome; Skin Cancer; Skin Cancer, Childhood; Skin Cancer (Melanoma); Skin Carcinoma, Merkel Cell; Small Cell Lung Cancer; Small Intestine Cancer; Soft Tissue Sarcoma, Adult; Soft Tissue Sarcoma, Childhood; Squamous Neck Cancer with Occult Primary, Metastatic; Stomach (Gastric) Cancer; Stomach (Gastric) Cancer, Childhood; Supratentorial Primitive Neuroectodermal Tumors, Childhood; T-Cell Lymphoma, Cutaneous; Testicular Cancer; Thymoma, Childhood; Thymoma, Malignant; Thyroid Cancer; Thyroid Cancer, Childhood; Transitional Cell Cancer of the Renal Pelvis and Ureter; Trophoblastic Tumor, Gestational; Unknown Primary Site, Cancer of, Childhood; Unusual Cancers of Childhood; Ureter and Renal Pelvis, Transitional Cell Cancer; Urethral Cancer; Uterine Sarcoma; Vaginal Cancer; Visual Pathway and Hypothalamic Glioma, Childhood; Vulvar Cancer; Waldenstrom's Macro globulinemia; and Wilms' Tumor.
Method according to embodiment 18, wherein the cancer is lung cancer, preferably non-small cell lung cancer (NSCLC).
Method according to any one of the preceding embodiments, wherein the sample of the patient comprises peripheral blood mono-nuclear cells (PBMCs).
Method according to any one of the preceding embodiments, wherein in step (b) a hierarchical clustering algorithm is applied.
Kit, diagnostic composition or device for the analysis of at least one marker gene set out in table 1 comprising at least one primer and/or probe selective for determining the expression level of at least one marker gene set out in table 1.
Kit, diagnostic composition or device of embodiment 22, further comprising an enzyme for primer elongation, nucleotides and/or labeling agents.
Microarray, comprising at least one probe selective for determining the expression level of at least one marker gene set out in table 1.
Use of a microarray according to embodiment 24 for determining the prognosis of a cancer patient.
Use of a kit, diagnostic composition or device according to embodiment 22 or 23 for determining the prognosis of a cancer patient.
| Number | Date | Country | Kind |
|---|---|---|---|
| PCT/EP2016/061829 | May 2016 | EP | regional |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2017/062694 | 5/24/2017 | WO | 00 |
