WO2018130332A1 - Mirna's for prognosing cutaneous t-cell lymphoma - Google Patents

Mirna's for prognosing cutaneous t-cell lymphoma Download PDF

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Publication number
WO2018130332A1
WO2018130332A1 PCT/EP2017/080204 EP2017080204W WO2018130332A1 WO 2018130332 A1 WO2018130332 A1 WO 2018130332A1 EP 2017080204 W EP2017080204 W EP 2017080204W WO 2018130332 A1 WO2018130332 A1 WO 2018130332A1
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mir
mirna
hsa
anyone
individual
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PCT/EP2017/080204
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French (fr)
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Lars Iversen
Lise Maria LINDAHL
FEENTVED Niels ØDUM
Søren BESENBACHER
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Aarhus Universitet
University Of Copenhagen
Region Midtjylland
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Publication of WO2018130332A1 publication Critical patent/WO2018130332A1/en

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates to methods of prognosing cutaneous T-cell lymphoma in an individual comprising determining the expression level of at least one miRNA selected from a group consisting of identified miRNAs; methods of determining a treatment regime of an individual having primary cutaneous T-cell lymphoma by determining the expression level of at least one of said miRNA's; and a kit comprising at least one probe or at least one pair of probe that specifically bind to a region of at least one of said miRNA's.
  • MF Mycosis fungoides
  • CCL cutaneous T-cell lymphomas
  • the aggressive form may account for patients who progress from the early to the advanced stages of MF during their disease cause and for patients having advanced disease at time of diagnosis.
  • the mortality increases in the advanced disease stages and require aggressive treatment. It remains a challenge at time of diagnosis to identify patients, who will progress from the early to the advanced stages of MF during their disease cause and have a worsened prognosis.
  • Existing clinical practice is to monitor the patient clinically and upon disease progression more aggressive treatment is initiated.
  • the clinical treatment guidelines provide recommendations according to the clinical stage of the disease (Trautinger F et al. European journal of cancer 2006; 42(8): 1014-30).
  • Other predictive factors for progression and prognosis have not yet been integrated in the treatment
  • CLIPi cutaneous lymphoma international prognostic index
  • the inventors of the present invention have developed a molecular prognostic classifier for patients having CTCL or MF at an early stage.
  • the inventors of the present invention Based on biopsies from patients diagnosed with early stage MF the inventors of the present invention have developed a miRNA prognostic classifier that may add substantial improvement of the existing clinical prognostic predictors in patients with early stage CTCL such as MF.
  • the present invention provides a method of prognosing cutaneous T-cell lymphoma in an individual, said method comprising:
  • determining the expression level of at least one miRNA in said test sample wherein the at least one miRNA is selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.
  • said prognosing includes determing the risk of disease progression.
  • said disease progression means that the stage of Mycosis fungoides progresses to stage IIB-IVB.
  • the present invention provides a method of determining whether an individual is at risk of developing an aggressive form of cutaneous T-cell lymphoma (CTCL), said method comprising:
  • determining the expression level of at least one miRNA in said test sample wherein the at least one miRNA is selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5
  • said individual has CTCL or is diagnosed with CTCL.
  • the term individual may be used interchangeably with patient.
  • the individual is a human being.
  • said CTCL is MF.
  • said test sample comprises tissue cells.
  • tissue cells are obtained from a
  • the method according to the present invention comprises determining the expression levels of at least two miRNA's. In another embodiment the method comprises determining the expression levels of at least three miRNAs. In yet another embodiment the method comprises determining the expression levels of at least 4, such as at least 5, at least 6, at least 7, at least 8, at least 9 or such as at least 10 miRNA's. In one embodiment the method according to the present invention comprises determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p. In another embodiment the method comprises determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p and miR-148a-3p.
  • the method comprises determining the expression level of at least two miRNA's selected from the group consisting of miR-106b-5p, miR-148a-3p and miR- 338-3p. In a particular embodiment the method comprises determining the expression level of miR-106b-5p and miR-148a-3p. In another particular embodiment the method comprises determining the expression level of miR-106b-5p, miR-148a-3p and miR- 338-3p.
  • said individual has Mycosis fungoides (MF) at an early stage.
  • said early stage is stage IA-IIA.
  • the risk of disease progression. in said individual is determined by calculating a risk score R.
  • the risk score R is a linear combination of one or more normalised Cp levels of one or more miRNAs. In a preferred embodiment R is calculated using the formula:
  • R ⁇ * Cpi + ⁇ 2 * Cp 2 + ....+ ⁇ ⁇ -1 * Cpn-1 + ⁇ ⁇ * Cp n .
  • Cpi ...Cp n refers to the normalized crossing point value for a given miRNA, wherein ⁇ - ⁇ ,.. ⁇ ⁇ are coefficients calculated by linear regression and wherein n is an integer and refers to the number of miRNA tested.
  • an individual having a high or an increased risk of disease progression is subjected to systemic treatment.
  • said systemic treatment can be selected from the group consisting of interferon alpha, bexarotene, methotrexate, corticosteroids, pegylated liposomal doxorubicin, histone deacetylase inhibitors (HDACi) such as eg. vorinostat or romidepsin, alemtuzumab and psoralen plus ultraviolet A light.
  • HDACi histone deacetylase inhibitors
  • said level(s) of miRNA is/are determined by amplifying a portion of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p
  • miR.148b.3p miR.18a.5p, miR.532.5p and miR.192.5p.
  • said level(s) of miRNA is/are determined using an oligonucleotide probe capable of binding to the amplified portion of said at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p,
  • miR.18a.5p miR.532.5p and miR.192.5p.
  • a second aspect of the present invention relates to a method of determining a treatment regime of an individual having cutaneous T-cell lymphoma said method comprising the steps of
  • said individual having a high risk of disease progression has Mycosis fungoides at stage IIB-IVB.
  • Said systemic treatment may for example be selected from the group consisting of interferon alpha, bexarotene, methotrexate, corticosteroids, pegylated liposomal doxorubicin, histone deacetylase inhibitors (HDACi) such as eg. vorinostat or romidepsin, alemtuzumab and psoralen plus ultraviolet A light.
  • HDACi histone deacetylase inhibitors
  • said individual is a human being.
  • a third aspect of the present invention relates to a kit for determining the risk of disease progression in an individual having cutaneous T-cell lymphoma, said kit comprising at least one probe or at least one pair of probe that specifically bind to a region of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p,
  • kit further comprises a microarray chip, wherein said probe(s) is/are located on said microarray chip.
  • said kit further comprises a QPCR Microfluidic Card.
  • said kit further comprises at least one additional component.
  • said additional component comprises means for extracting RNA, such as miRNA, from a sample.
  • said additional component comprises reagents for performing microarray analysis.
  • said additional component comprises reagents for performing QPCR analysis.
  • Figure 1A Hierarchical clustering of the 82 mycosis fungoides patients in the discovery cohort compared with the 20 age- and sex matched healthy controls.
  • 1 B LASSO coefficient profiles of the strongest disease-related miRNAs to predict disease progression.
  • FIG. 1 Leave-one-out cross validation for turning parameter selection in the LASSO model for the three miRNAs.
  • the partial likelihood deviance is plottet against the LASSO tuning parameter, lambda.
  • the shaded band indicate the standard error (SE) of the partial likelihood deviance.
  • Figure 3 Risk score by the three-miRNA classifier, time dependent ROC curves and Kaplan-Meier progression free survival curves in the discovery cohort and the validation cohort. Risk score, time dependent ROC curve and progression free survival curves for the discovery cohort (A-C) and the validation cohort (D-F). The area under the curve (AUC) was calculated for the ROC curves to assess prognostic accuracy.
  • Figure 5 Accuracy of the three-miRNA classifier, clinical prognostic factors and single miRNAs from the classifier by time-dependent ROC curves of progression free survival.
  • A Comparisons of the prognostic accuracy of the three-miRNA classifier and existing clinical prognostic factors: sex, age, T1 b or T2b, clinical stage and CLIPi.
  • B Comparisons of the prognostic accuracy of the three-miRNA classifier and existing clinical prognostic factors: sex, age, T1 b or T2b, clinical stage and CLIPi.
  • FIG. 1 Time to progression for each individual patient.
  • the horizontal line illustrates 5 years after diagnosis; 42 patients (82%) progressed within the first 5 years after their diagnosis.
  • amplification refers to the process wherein a plurality of exact copies of one or more gene loci or gene portions (template) is synthesised.
  • amplification of a template comprises the process wherein a template is copied by a nucleic acid polymerase or polymerase homologue, for example a DNA polymerase or an RNA polymerase.
  • templates may be amplified using reverse transcription, the polymerase chain reaction (PCR), ligase chain reaction (LCR), in vivo amplification of cloned DNA, isothermal amplification techniques, and other similar procedures capable of generating a complementing nucleic acid sequence.
  • a 'probe' as used herein refers to a hybridization probe.
  • a hybridization probe is a (single-stranded) fragment of DNA or RNA of variable length (usually 20-1000 bases long), which is used in DNA or RNA samples to detect the presence of nucleotide sequences (the DNA target) that are complementary to the 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.
  • the probe is tagged (or labelled) with a molecular marker of either radioactive or fluorescent molecules. DNA sequences or RNA transcripts that have moderate to high sequence similarity to the probe are then detected by visualizing the hybridized probe.
  • Hybridization probes used in DNA microarrays refer to DNA covalently attached to an inert surface, such as coated glass slides or gene chips, and to which a mobile cDNA target is hybridized.
  • a double stranded nucleic acid contains two strands that are complementary in sequence and capable of hybridizing to one another.
  • a gene is defined in terms of its coding strand, but in the context of the present invention, an oligonucleotide primer, which hybridize to a gene as defined by the sequence of its coding strand, also comprise oligonucleotide primers, which hybridize to the complement thereof.
  • nucleotide as used herein defines a monomer of RNA or DNA.
  • a nucleotide is a ribose or a deoxyribose ring attached to both a base and a phosphate group. Both mono-, di-, and tri-phosphate nucleosides are referred to as nucleotides.
  • oligonucleotide refers to oligonucleotides of both natural and/or non-natural nucleotides, including any combination thereof. The natural and/or non-natural nucleotides may be linked by natural phosphodiester bonds or by non- natural bonds.
  • oligonucleotides comprise only natural nucleotides linked by phosphodiester bonds.
  • the oligomer or polymer sequences of the present invention are formed from the chemical or enzymatic addition of monomer subunits.
  • the term "oligonucleotide” as used herein includes linear oligomers of natural or modified monomers or linkages, including deoxyribonucleotides, ribonucleotides, anomeric forms thereof, peptide nucleic acid monomers (PNAs), locked nucleotide acid monomers (LNA), and the like, capable of specifically binding to a single stranded polynucleotide tag by way of a regular pattern of monomer-to-monomer interactions, such as Watson-Crick type of base pairing, base stacking, Hoogsteen or reverse Hoogsteen types of base pairing, or the like.
  • monomers are linked by phosphodiester bonds or analogs thereof to form oligonucleotides ranging in size from a few monomeric units, e.g. 3-4, to several tens of monomeric units, e.g. 40-60.
  • oligonucleotide is represented by a sequence of letters, such as
  • AGTCCTG it will be understood that the nucleotides are in 5' ⁇ 3' order from left to right and the "A” denotes deoxyadenosine, “C” denotes deoxycytidine, “G” denotes deoxyguanosine, and “T” denotes thymidine, unless otherwise noted.
  • A denotes deoxyadenosine
  • C denotes deoxycytidine
  • G denotes deoxyguanosine
  • T denotes thymidine, unless otherwise noted.
  • the nucleotides of the top strand are in 5' ⁇ 3' order from left to right and the nucleotides of the bottom strand are then in 3' ⁇ 5' order from left to right.
  • oligonucleotides of the invention comprise the four natural nucleotides; however, they may also comprise methylated or non-natural nucleotide analogs.
  • nucleic acid or “nucleic acid molecule” refers to polynucleotides, such as deoxyribonucleic acid (DNA) or ribonucleic acid (RNA), oligonucleotides, fragments generated by the polymerase chain reaction (PCR), and fragments generated by any of ligation, scission, endonuclease action, and exonuclease action.
  • Nucleic acid molecules can be composed of monomers that are naturally-occurring nucleotides (such as DNA and RNA), or analogs of naturally-occurring nucleotides (e.g. alpha- enantiomeric forms of naturally-occurring nucleotides), or a combination of both.
  • naturally-occurring nucleotides such as DNA and RNA
  • analogs of naturally-occurring nucleotides e.g. alpha- enantiomeric forms of naturally-occurring nucleotides
  • Modified nucleotides can have alterations in sugar moieties and/or in pyrimidine or purine base moieties.
  • Sugar modifications include, for example, replacement of one or more hydroxyl groups with halogens, alkyl groups, amines, and azido groups, or sugars can be functionalized as ethers or esters.
  • the entire sugar moiety can be replaced with sterically and electronically similar structures, such as aza-sugars and carbocyclic sugar analogs.
  • modifications in a base moiety include alkylated purines and pyrimidines, acylated purines or pyrimidines, or other well-known heterocyclic substitutes.
  • Nucleic acid monomers can be linked by phosphodiester bonds or analogs of such linkages.
  • nucleic acid molecule also includes e.g. so-called “peptide nucleic acids,” which comprise naturally-occurring or modified nucleic acid bases attached to a polyamide backbone. Nucleic acids can be either single stranded or double stranded.
  • 'nucleic acid' is meant to comprise antisense oligonucleotides (ASO), small inhibitory RNAs (siRNA), short hairpin RNA (shRNA) and microRNA (miRNA).
  • ASO antisense oligonucleotides
  • small inhibitory RNAs small inhibitory RNAs
  • shRNA short hairpin RNA
  • miRNA microRNA
  • microRNA miRNA
  • miRNAs are single-stranded RNA molecules of about 19-25 nucleotides in length, which regulate gene expression. miRNAs are either expressed from non-protein-coding transcripts or mostly expressed from protein coding transcripts.
  • Mature miRNA molecules are partially complementary to one or more messenger RNA (mRNA) molecules, and their main function is to inhibit gene expression. This may occur by preventing mRNA translation or increasing mRNA turnover/degradation.
  • mRNA messenger RNA
  • the transcripts encoding miRNAs are much longer than the processed mature miRNA molecule; miRNAs are first transcribed as primary transcripts or pri-miRNA with a cap and poly-A tail by RNA polymerase II and processed to short, 70-nucleotide stem-loop structures known as pre-miRNA in the cell nucleus.
  • This processing is performed in animals (including humans) by a protein complex known as the Microprocessor complex, consisting of the ribonuclease III Drosha and the double-stranded RNA binding protein Pasha.
  • These pre-miRNAs are then exported to the cytoplasm by Exportin-5/Ran-GTP and processed to mature miRNAs by interaction with the ribonuclease III Dicer and separation of the miRNA duplexes.
  • the mature single- stranded miRNA is incorporated into a RNA-induced silencing complex (RlSC)-like ribonucleoprotein particle (miRNP).
  • RlSC RNA-induced silencing complex
  • miRNP RNA-induced silencing complex
  • the RISC complex is responsible for the gene silencing observed due to miRNA expression and RNA interference.
  • the pathway is different for miRNAs derived from intronic stem-loops; these are processed by Dicer but not by Drosha.
  • Dicer cleaves the pre-miRNA stem-loop, two complementary short RNA molecules are formed, but only one is integrated into the RISC complex.
  • This strand is known as the guide strand and is selected by the argonaute protein, the catalytically active RNase in the RISC complex, on the basis of the stability of the 5' end.
  • the remaining strand known as the anti-guide or passenger strand, is degraded as a RISC complex substrate.
  • miRNAs base pair with their complementary mRNA molecules. This may induce mRNA degradation by argonaute proteins, the catalytically active members of the RISC complex, or it may inhibit mRNA translation into proteins without mRNA degradation.
  • miRNAs The function of miRNAs appears to be mainly in gene regulation.
  • a miRNA is (partly) complementary to a part of one or more mRNAs.
  • Animal (including human) miRNAs are usually complementary to a site in the 3' UTR.
  • the annealing of the miRNA to the mRNA then inhibits protein translation, and sometimes facilitates cleavage of the mRNA (depending on the degree of complementarity).
  • the formation of the double-stranded RNA through the binding of the miRNA to mRNA inhibits the mRNA transcript through a process similar to RNA interference (RNAi).
  • miRNAs may regulate gene expression post-transcriptionally at the level of translational inhibition at P-bodies.
  • miRNAs are regions within the cytoplasm consisting of many enzymes involved in mRNA turnover; P bodies are likely the site of miRNA action, as miRNA-targeted mRNAs are recruited to P bodies and degraded or sequestered from the translational machinery. In other cases it is believed that the miRNA complex blocks the protein translation machinery or otherwise prevents protein translation without causing the mRNA to be degraded. miRNAs may also target methylation of genomic sites which correspond to targeted mRNAs. miRNAs function in association with a complement of proteins collectively termed the miRNP (miRNA ribonucleoprotein complex).
  • miRNP miRNA ribonucleoprotein complex
  • miRNA names are assigned to experimentally confirmed miRNAs before publication of their discovery.
  • the prefix “mir” is followed by a dash and a number, the latter often indicating order of naming.
  • mir-123 was named and likely discovered prior to mir-456.
  • the uncapitalized “mir-” refers to the pre-miRNA, while a capitalized “miR-” refers to the mature form.
  • miRNAs with nearly identical sequences bar one or two nucleotides are annotated with an additional lower case letter. For example, miR-123a would be closely related to miR-123b.
  • miRNAs that are 100% identical but are encoded at different places in the genome are indicated with additional dash-number suffix: miR-123-1 and miR-123-2 are identical but are produced from different pre-miRNAs. Species of origin is designated with a three-letter prefix, e.g., hsa-miR-123 would be from human (Homo sapiens) and oar-miR-123 would be a sheep (Ovis aries) miRNA. Other common prefixes include V for viral (miRNA encoded by a viral genome) and 'd' for Drosophila miRNA.
  • microRNAs originating from the 3' or 5' end of a pre-miRNA are denoted with a -3p or -5p suffix. (In the past, this distinction was also made with 's' (sense) and 'as' (antisense)).
  • an asterisk following the name indicates that the miRNA is an anti-miRNA to the miRNA without an asterisk (e.g. miR-123 * is an anti-miRNA to miR-123).
  • hsa-miR-123 is identical to miR-123, and that this may also be denoted miR.123 as well as miR-123 or hsa-miR-123 or hsa.miR.123.
  • let is used instead of "miR” in the nomenclature, such as for example hsa.let.7i.5p. These microRNAs were identified before the standard nomenclature system was introduced.
  • miRBase is the central online repository for microRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via miRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via miRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via miRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via miRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via miRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via miRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via miRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via miRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via
  • miRNA-106b-5p miR-125a, miR-148a-3p and miR.92a-3p refer to the human miR sequences found in miR registry database release 12.0 or later and hosted by Sanger Institute, UKas. All miRs are human miR sequences commonly referred to by the prefix "hsa-", e.g.
  • hsa-miR-125a refer to the human miR- 125a.
  • Cutaneous T cell lymphoma is a class of non-Hodgkin lymphoma, which is a type of cancer of the immune system. Unlike most non-Hodgkin lymphomas, CTCL is caused by a mutation of T cells. The malignant T cells in the body initially migrate to the skin, causing various lesions to appear. These lesions change shape as the disease progresses, typically beginning as what appears to be a rash which can be very itchy and eventually forming plaques and tumors before metastasizing to other parts of the body. CTCL is divided into different stages.
  • CTCL The stage of CTCL describes how much of the skin is affected , whether formation of a tumor has occured and whether it has spread anywhere else.
  • CTCL develops very slowly.
  • the symptoms can remain the same for many years and most people never progress beyond the first stage.
  • some people don't experience the early stages of CTCL and their first symptoms may be tumours (raised lumps) on the skin.
  • CTCL The stages of CTCL are described below:
  • Stage 1 There are red patches and/or raised red patches (plaques) on the skin. This stage is sometimes divided into:
  • Stage 2A Skin symptoms are the same as in stage 1. Some lymph nodes are enlarged, but the lymphoma cells have not spread there.
  • Stage 2B There may be one or more tumours on the skin.
  • the lymph nodes may or may not be affected.
  • Stage 3 More than 80% of the skin is red (erythroderma).
  • the lymph nodes may or may not be affected.
  • Stage 4 There may be any of the skin symptoms described in the previous stages.
  • the lymphoma has spread to other organs in the body such as the liver. Lymphoma cells may or may not have spread to the lymph nodes and/or blood.
  • MF Mycosis fungoides
  • a medical history, physical exam, and skin biopsy are important for diagnosis.
  • a physician will examine lymph nodes, order various blood tests, and may conduct other screening tests, such as a chest x-ray or a computed axial tomography (CAT) scan. Scans are usually not needed for those with the earliest stages of the disease.
  • CAT computed axial tomography
  • Mycosis fungoides is difficult to diagnose in its early stages because the symptoms and skin biopsy findings are similar to those of other skin conditions.
  • the present invention provides a method of prognosing cutaneous T-cell lymphoma in an individual, said method comprising:
  • determining the expression level of at least one miRNA in said test sample wherein the at least one miRNA is selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.
  • Preferablt said prognosing includes determing the risk of disease progression.
  • the present invention provides a method of determining whether an individual is at risk of developing an aggressive form of cutaneous T-cell lymphoma (CTCL), said method comprising: iii. providing a test sample from said individual;
  • determining the expression level of at least one miRNA in said test sample wherein the at least one miRNA is selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5
  • the expression level of at least one of said miRNAs in one embodiment is measured in a sample, such as a tissue sample, from an individual, and said miRNA expression level as compared to a control or baseline level is then associated with the risk of disease progression in an individual having cutaneous T-cell lymphoma.
  • said miRNAs are used in combination; i.e. the expression level of at least the two miRNAs according to the method above are both used in combination to prognose cutaneous T-cell lymphoma and/or to determine whether an individual is at risk of developing an aggressive form of cutaneous T-cell lymphoma.
  • the present invention provides a method for distinguishing aggressive forms of cutaneous T-cell lymphoma from non-aggressive form.
  • the method of the present invention comprises determining the expression levels of at least two miRNA's selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p
  • the method as defined herein comprises determining the expression levels of at least three miRNA's selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p,
  • the method as defined herein comprises determining the expression levels of at least 4, such as at least 5, at least 6, at least 7, at least 8, at least 9 or such as at least 10 miRNA's selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p
  • miR.148b.3p miR.18a.5p, miR.532.5p and miR.192.5p.
  • the method as defined herein comprises determining the expression levels of at least 1 1 , such as at least 12, at least 13, at least 14, at least 15, or such as at least 20 miRNA's selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p,
  • miR.130a.3p miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p,
  • miR.18a.5p miR.532.5p and miR.192.5p.
  • the method of the present invention comprises determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p. In another preferred embodiment the method of the present invention comprises determining the expression level of at least two miRNA's selected from the group consisting of miR-106b-5p, miR- 148a-3p and miR-338-3p. In yet another preferred embodiment the method comprises determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p and miR-148a-3p.
  • the method comprises determining the expression level of miR-106b-5p and miR-148a-3p. In another particular embodiment method comprises determining the expression level of miR-106b-5p, miR-148a-3p and miR-338-3p.
  • the embodiments defined above may be combined with determining the expressions level of additional miRNA's as defined above.
  • the method defined herein comprises determining the expression levels of at least one miRNA selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNA's selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miRNA's selected
  • miR.139.5p miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
  • the method comprises determining the expression levels of at least two miRNA selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNAs selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p,
  • miR.19b.3p let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, mi
  • the method comprises determining the expression levels of miR-106b-5p, miR-148a-3p and miR-338-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNAs selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p
  • the method defined herein comprises determining the expression levels of at least one miRNA selected from the group consisting of miR- 106b-5p and miR-148a-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNA's selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101 .3p, miR.22.3p,
  • the method defined herein comprises determining the expression levels of miR-106b-5p and miR-148a-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNA's selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3
  • miR.130a.3p miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p,
  • miR.18a.5p miR.532.5p and miR.192.5p.
  • a biomarker such as a miRNA biomarker
  • a biomarker may be correlated to a certain condition based on differences in miRNA expression levels between a sample and a control. If a certain miRNA biomarker is found to be altered in a sample as compared to a (normal) control level, the sample has a certain probability of being associated with a certain condition. Thus, it may be the relationship between the expression levels of two or more biomarkers that is telling of a particular condition; i.e. the relative difference in expression levels between two biomarkers.
  • said method further comprises a step of correlating the miRNA expression level(s) as defined herein to a predetermined control level.
  • any given miRNA biomarker of the present invention may in one embodiment be either increased or decreased in a sample from an individual or a patient with CTCL such as MF as compared to a control sample.
  • the method according to the present invention further comprises comparing the expression level of at least one miRNA as defined herein in the test sample to the expression level of the corresponding miRNA in a control sample.
  • the method of the present invention may in one embodiment comprise comparing the expression levels of the specific combinations of miRNAs as defined herein in the test sample to the expression levels of the corresponding miRNAs in a control sample.
  • expression levels of one or more of the miRNAs as defined in the embodiments herein above is/are altered as compared to the expression level(s) of the corresponding miRNA(s) in a control sample. It is contemplated that a difference in the expression levels of said at least one miRNA in the test sample and in the control sample is indicative of disease progression or that said individual has an increased risk of developing an aggressive form of CTCL.
  • control sample is obtained from a healthy individual or from an individual not having CTCL.
  • control sample comprises tissue cells.
  • control sample is a tissue sample.
  • the present invention relates to a method of prognosing CTCL in an individual.
  • the individual has CTCL or is diagnosed with CTCL.
  • said individual has CTCL at an early stage.
  • said individual has MF, preferably MF at an early stage. It is preferred that said early stage is stage IA-IIA.
  • “Individual” refers to vertebrates, particular members of the mammalian species, preferably primates including humans. In a preferred embodiment said individual is a human being. As used herein, 'subject', 'individual' and “patient” may be used interchangeably.
  • test sample according to the present invention is extracted from an individual and used for miRNA profiling for the subsequent prognosis of CTCL.
  • test sample is obtained from an individual having CTCL.
  • control sample is preferably obtained from a healthy individual or an individual not having CTCL.
  • the individual may be any animal, such as a mammal, including human beings. In a preferred embodiment, the individual is a human being.
  • the test sample and/or the control sample can be a body fluid sample such as a blood sample, a urine sample, a faecal sample, a serum sample or a saliva sample.
  • the sample may also be obtained by a skin swabs, nasal swabs or cheek epithelium swabs.
  • the sample is a skin biopsy or a lymph node biopsy.
  • the biopsy may be a small sample of tissue that is taken with a needle or minor surgery.
  • the test sample is a biopsy of the affected skin or the skin tumour. The doctor may for example shave off a thin slice of affected skin, for example where rash or tumour has appeared.
  • the sample comprises tissue cells.
  • the sample is a tissue sample.
  • test sample and the control sample are obtained in the same way.
  • control sample and the test sample comprise tissue cells or are tissue samples or more preferably skin biopsies. Several skin sample or biopsies from different areas of the body may be taken.
  • the tissues or the skin biopsies may be examined under a microscope to determine the stage of CTCL.
  • the sample extracted from the individual may be analysed essentially immediately, or it may be stored prior to analysis for a variable period of time and at various temperature ranges.
  • the sample is stored at a temperature of between -200°C to 37°C, such as between -200 to -100°C, for example -100 to -50°C, such as -50 to -25°C, for example -25 to -10°C, such as -10 to 0°C, for example 0 to 10°C, such as 10 to 20°C, for example 20 to 30°C, such as 30 to 37°C prior to analysis.
  • the sample is stored at -20°C and/or -80°C.
  • the sample is stored for between 15 minutes and 100 years prior to analysis, such as between 15 minutes and 1 hour, for example 1 to 2 hours, such as 2 to 5 hours, for example 5 to 10 hours, such as 10 to 24 hours, for example 24 hours to 48 hours, such as 48 to 72 hours, for example 72 to 96 hours, such as 4 to 7 days, such as 1 week to 2 weeks, such as 2 to 4 weeks, such as 4 weeks to 1 month, such as 1 month to 2 months, for example 2 to 3 months, such as 3 to 4 months, for example 4 to 5 months, such as 5 to 6 months, for example 6 to 7 months, such as 7 to 8 months, for example 8 to 9 months, such as 9 to 10 months, for example 10 to 1 1 months, such as 1 1 to 12 months, for example 1 year to 2 years, such as 2 to 3 years, for example 3 to 4 years, such as 4 to 5 years, for example 5 to 6 years, such as 6 to 7 years, for example 7 to 8 years, such as 8 to 9 years, for example 9 to 10 years, such as
  • the sample is stored for a few days.
  • a collection media according to the present invention is any media suitable for preserving and/or collecting a sample for immediate or later analysis.
  • said collection media is a solution suitable for sample preservation and/or later retrieval of RNA (such as miRNA) from said sample.
  • the collection media is an RNA preservation solution or reagent suitable for containing samples without the immediate need for cooling or freezing the sample, while maintaining RNA integrity prior to extraction of RNA (such as miRNA) from the sample.
  • RNA preservation solution or reagent may also be known as RNA stabilization solution or reagent or RNA recovery media, and may be used
  • the RNA preservation solution may penetrate the harvested cells of the collected sample to retard RNA degradation to a rate dependent on the storage temperature.
  • a biopsy sample is obtained from the individual and embedded in paraffin. This sample is preferably stored at room temperature.
  • the RNA preservation solution may be any commercially available solutions or it may be a solution prepared according to available protocols.
  • RNA preservation solutions may for example be selected from RNAIater® (Ambion and Qiagen), PreservCyt medium (Cytyc Corp),
  • RNA stabilizing solution may be retrieved from the internet (e.g. L.A. Clarke and M.D. Amaral: 'Protocol for RNase-retarding solution for cell samples', provided through The European Working Group on CFTR Expression), or may be produced and/or optimized according to techniques known to the skilled person.
  • the collection media will penetrate and lyse the cells of the sample immediately, including reagents and methods for isolating RNA (such as miRNA) from a sample that may or may not include the use of a spin column.
  • RNA such as miRNA
  • Other collection media comprises any media such as water, sterile water, denatured water, saline solutions, formalin, buffers, PBS, TBS, Allprotect Tissue Reagent (Qiagen), cell culture media such as RPMI-1640, DMEM (Dulbecco's Modified Eagle Medium), MEM (Minimal Essential Medium), IMDM (Iscove's Modified Dulbecco's Medium), BGjB (Fitton-Jackson modification), BME (Basal Medium Eagle), Brinster's BMOC-3 Medium, CMRL Medium, C0 2 -Independent Medium, F-10 and F-12 Nutrient Mixture, GMEM (Glasgow Minimum Essential Medium), IMEM (Improved Minimum Essential Medium), Leibovitz's L-15 Medium, McCoy's 5A Medium, MCDB 131 Medium, Medium 199, Opti-MEM, Waymouth's MB 752/1 , Williams' Media E, Tyrode'
  • the sample is collected, it is subjected to analysis.
  • the sample is initially used for isolating or extracting RNA according to any conventional methods known in the art; followed by an analysis of the miRNA expression in said sample.
  • the RNA isolated from the sample may be total RNA, mRNA, microRNA, tRNA, rRNA or any type of RNA.
  • Conventional methods and reagents for isolating RNA from a sample are well known to the skilled person and commercially available.
  • kits for isolating RNA from biopsies embedded in paraffin is commercially available and well known to the skilled person.
  • the RNA may be further amplified, cleaned-up, concentrated, DNase treated, quantified or otherwise analysed or examined such as by agarose gel electrophoresis, absorbance spectrometry or Bioanalyser analysis (Agilent) or subjected to any other post-extraction method known to the skilled person.
  • Microarray analysis Agilent
  • the isolated RNA may be analysed by microarray analysis.
  • the expression level of one or more miRNAs is determined by the microarray technique.
  • a microarray is a multiplex technology that consists of an arrayed series of thousands of microscopic spots of DNA oligonucleotides or antisense miRNA probes, called features, each containing picomoles of a specific oligonucleotide sequence. This can be a short section of a gene or other DNA or RNA element that are used as probes to hybridize a DNA or RNA sample (called target) under high-stringency conditions.
  • Probe-target hybridization is usually detected and quantified by fluorescence-based detection of fluorophore-labeled targets to determine relative abundance of nucleic acid sequences in the target.
  • the probes are attached to a solid surface by a covalent bond to a chemical matrix (via epoxy-silane, amino-silane, lysine, polyacrylamide or others).
  • the solid surface can be glass or a silicon chip, in which case they are commonly known as gene chip.
  • DNA arrays are so named because they either measure DNA or use DNA as part of its detection system.
  • the DNA probe may however be a modified DNA structure such as LNA (locked nucleic acid).
  • the microarray analysis is used to detect microRNA, known as microRNA or miRNA expression profiling.
  • the microarray for detection of microRNA may be a microarray platform, wherein the probes of the microarray may be comprised of antisense miRNAs or DNA
  • the microarray for detection of microRNA may be a commerciaiiy available array platform, such as NCodeTM miRNA Microarray Expression Profiling (Invitrogen), miRCURY LNATM microRNA Arrays (Exiqon), microRNA Array (Agilent), ⁇ ® Microfluidic Biochip Technology (LC Sciences), MicroRNA Profiling Panels (lllumina), Geniom® Biochips (Febit Inc.), microRNA Array (Oxford Gene Technology), Custom AdmiRNATM profiling service (Applied Biological Materials Inc.), microRNA Array (Dharmacon - Thermo Scientific), LDA TaqMan analyses (Applied Biosystems), Taqman microRNA Array (Applied Biosystems), BiomarkTM HD System (Fluidigm System) using TaqMan reagents or any other commercially available array
  • Microarray analysis may comprise all or a subset of the steps of RNA isolation, RNA amplification, reverse transcription, target labelling, hybridisation onto a microarray chip, image analysis and normalisation, and subsequent data analysis; each of these steps may be performed according to a manufacturers protocol.
  • any of the methods as disclosed herein above may further comprise one or more of the steps of:
  • the microarray for detection of microRNA is custom made.
  • a probe or hybridization probe is a fragment of DNA or RNA of variable length, which is used to detect in DNA or RNA samples the presence of nucleotide sequences (the target) that are complementary to the sequence in the probe.
  • the target is a sense miRNA sequence in a sample (target) and an antisense miRNA 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.
  • the probe or the sample is tagged (or labeled) with a molecular marker.
  • Hybridization probes used in microarrays refer to nucleotide sequences covalently attached to an inert surface, such as coated glass slides, and to which a mobile target is hybridized. Depending on the method the probe may be synthesised via phosphoramidite technology or generated by PCR amplification or cloning (older methods). To design probe sequences, a probe design algorithm may be used to ensure maximum specificity (discerning closely related targets), sensitivity (maximum hybridisation intensities) and normalised melting temperatures for uniform hybridisation.
  • said level(s) of miRNA is/are determined by amplifying a portion of one or more of the miRNA(s) as defined in the embodiments herein and above. In one embodiment of the present invention said level(s) of miRNA is/are determined by amplifying a portion of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miRNA.106b.5
  • said level(s) of miRNA is/are determined using a probe capable of binding to one or more of the miRNA(s) as defined in the embodiments herein and above.
  • said level(s) of miRNA is/are determined using a probe capable of binding to at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p,
  • said probe(s) or probe set(s) bind to the amplified portion of said miRNA(s).
  • 1 to 2 probes or probe set is used per miRNA to be measured, such as 2 to 3 probes, for example 3 to 4 probes, such as 4 to 5 probes, for example 5 to 6 probes, such as 6 to 7 probes, for example 7 to 8 probes, such as 8 to 9 probes or probe sets per miRNA of the present invention to be measured.
  • 1 probe or probe set is used for at least one miRNA to be measured, such as 2 probes, for example 3 probes, such as 4 probes, for example 5 probes, such as 6 probes, for example 7 probes, for example 8 probes or probe sets for at least one miRNA of the present invention to be measured.
  • a probe set is a collection of two or more probes designed to interrogate or measure a given sequence.
  • 1 probe or probe set is used per miRNA to be measured.
  • the isolated RNA may be analysed by quantitative ('real-time') PCR (QPCR).
  • QPCR quantitative polymerase chain reaction
  • the expression level of one or more miRNAs is determined by the quantitative polymerase chain reaction (QPCR) technique.
  • Real-time polymerase chain reaction also called quantitative polymerase chain reaction (Q-PCR/qPCR/RT-QPCR) or kinetic polymerase chain reaction
  • Q-PCR/qPCR/RT-QPCR quantitative polymerase chain reaction
  • kinetic polymerase chain reaction is a tech based on the polymerase chain reaction, which is used to amplify and simultaneously quantify a targeted DNA molecule. It enables both detection and quantification (as absolute number of copies or relative amount when normalized to DNA input or additional normalizing genes) of a specific sequence in a DNA sample.
  • the procedure follows the general principle of polymerase chain reaction; its key feature is that the amplified DNA is quantified as it accumulates in the reaction in real time after each amplification cycle.
  • Two common methods of quantification are the use of fluorescent dyes that intercalate with double-stranded DNA, and modified DNA oligonucleotide probes that fluoresce when hybridized with a complementary DNA.
  • mRNA messenger RNA
  • miRNA miRNA
  • a positive reaction is detected by accumulation of a fluorescent signal.
  • the Ct cycle threshold
  • Ct- values are inversely proportional to the amount of target nucleic acid in the sample (i.e. the lower the Ct-value the greater the amount of target nucleic acid in the sample).
  • Most real time assays undergo 40 cycles of amplification.
  • Ct-values ⁇ 29 are strong positive reactions indicative of abundant target nucleic acid in the sample.
  • Ct-values of 30-37 are positive reactions indicative of moderate amounts of target nucleic acid.
  • Ct-values of 38-40 are weak reactions indicative of minimal amounts of target nucleic acid which could represent an infection state or
  • the QPCR may be performed using chemicals and/or machines from a commercially available platform.
  • the QPCR may be performed using QPCR machines from any commercially available platform; such as Prism, geneAmp or StepOne Real Time PCR systems (Applied Biosystems), LightCycler (Roche), RapidCycler (Idaho Technology), MasterCycler (Eppendorf), BioMarkTM HD System (Fluidigm), iCycler iQ system, Chromo 4 system, CFX, MiniOpticon and Opticon systems (Bio-Rad), SmartCycler system (Cepheid), RotorGene system (Corbett Lifescience), MX3000 and MX3005 systems (Stratagene), DNA Engine Opticon system (Qiagen), Quantica qPCR systems (Techne), InSyte and Syncrom cycler system (BioGene), DT-322 (DNA Technology), Exicycler Notebook Thermal cycler, TL998 System (lanlong), Line-Gene-K systems (Bioer Technology), or any other commercially available platform.
  • Prism GeneAmp or Step
  • the QPCR may be performed using chemicals from any commercially available platform, such as NCode EXPRESS qPCR or EXPRESS qPCR (Invitrogen), Taqman or SYBR green qPCR systems (Applied Biosystems), Real-Time PCR reagents
  • the QPCR reagents and detection system may be probe-based, or may be based on chelating a fluorescent chemical into double-stranded oligonucleotides.
  • the QPCR reaction may be performed in a tube; such as a single tube, a tube strip or a plate, or it may be performed in a microfluidic card in which the relevant probes and/or primers are already integrated.
  • a Microfluidic card allows high throughput, parallel analysis of mRNA or miRNA expression patterns, and allows for a quick and cost-effective investigation of biological pathways.
  • the microfluidic card may be a piece of plastic that is riddled with micro channels and chambers filled with the probes needed to translate a sample into a diagnosis.
  • a sample in fluid form is injected into one end of the card, and capillary action causes the fluid sample to be distributed into the microchannels.
  • the microfluidic card is then placed in an appropriate device for processing the card and reading the signal.
  • the isolated RNA may be analysed by northern blotting.
  • the expression level of one or more miRNAs is determined by the northern blot technique.
  • a northern blot is a method used to check for the presence of a RNA sequence in a sample.
  • Northern blotting combines denaturing agarose gel or polyacrylamide gel electrophoresis for size separation of RNA with methods to transfer the size-separated RNA to a filter membrane for probe hybridization.
  • the hybridization probe may be made from DNA or RNA.
  • the isolated RNA is analysed by nuclease protection assay.
  • the isolated RNA may be analysed by Nuclease protection assay.
  • Nuclease protection assay is a technique used to identify individual RNA molecules in a heterogeneous RNA sample extracted from cells. The technique can identify one or more RNA molecules of known sequence even at low total concentration.
  • the extracted RNA is first mixed with antisense RNA or DNA probes that are
  • RNA complementary to the sequence or sequences of interest and the complementary strands are hybridized to form double-stranded RNA (or a DNA-RNA hybrid).
  • the mixture is then exposed to ribonucleases that specifically cleave only s/ng/e-stranded RNA but have no activity against double-stranded RNA.
  • susceptible RNA regions are degraded to very short oligomers or to individual nucleotides; the surviving RNA fragments are those that were
  • Risk score To determine whether a patient or an individual is at risk of developing an aggressive form of cutaneous T-cell lymphoma a risk score R can be calculated.
  • the risk of disease progression in said individual is determined by calculating a risk score R.
  • the risk score R is defined by the following formula:
  • the risk of disease progression in said individual is determined by calculating a risk score R.
  • Cp refers to the normalized Cp value for a given miRNA.
  • n is an integer and refers to the number of miRNAs tested.
  • the coefficients, ⁇ - ⁇ , ⁇ ⁇ are calculated by fitting a multivariate Cox proportional hazards model (Cox DR. Regression models and life tables (with discussion) J R Statist Soc B.
  • h(t) ho(t) * exp( ⁇ * Cpi + ⁇ 2 * Cp 2 + ⁇ 3 * Cp 3 + ....+ ⁇ ⁇ - ⁇ * Cp n- i + ⁇ ⁇ * Cp n ) where the hazard function h(t) is dependent on the Cp values and h 0 (t) is a baseline hazard.
  • the LASSO method was used to shrink the coefficients and reduce the number of variables in the model (Tibshirani R. The lasso method for variable selection in the Cox model. Stat Med. 1997 Feb 28;16(4):385-95).
  • a cut off value is determined to discriminate patients with high risk and low risk of disease progression.
  • the cutoff can for example be set so that the number of high-risk individuals in the entire cohort matches the number of individuals in the entire cohort who developed disease progression.
  • disease progression means progression of CTCL such as MF to a more aggressive form.
  • said disease progression means that the stage of CTCL or MF progresses to stage IIB-IVB.
  • An individual having a risk score R above the cut off value may be subjected to intensified surveillance and/or systemic treatment.
  • Systemic treatment may for example include chemotherapy where the individual or the patient is treated with medicines to kill cancer cells.
  • Medicines may for example be put on the skin as a cream or gel.
  • medicines may be taken by mouth or injected into a vein, intramuscularly or subcutaneously so they can reach cancer cells all over the body.
  • retinoids may include retinoids, HDAC inhibitors, corticosteroids, targeted medicine including biological drugs such as but not limited to antibodies or immune therapy. Some of these are applied to the skin. Others are taken by mouth or given as a shot (injection).
  • the systemic treatment is radiation therapy.
  • Radiation therapy may include X-rays to kill cancer cells and shrink tumors.
  • Total skin electron beam therapy (or TSEBT) may be used to treat skin lymphoma.
  • systemic treatment is photodynamic therapy.
  • Photodynamic therapy uses certain types of UV (ultraviolet) light and medicines called psoralens to kill cancer cells.
  • the systemic treatment is Extracorporeal photopheresis (ECP).
  • ECP is used to kill lymphoma cells in the blood.
  • the blood is sent through a machine that exposes it to a special UV (ultraviolet) light.
  • the light kills the lymphoma cells, and the blood is then returned to the body.
  • the expression levels of the miRNA biomarkers are correlated with the risk of progression of CTCL, such as the risk of progression to an aggressive stage of CTCL. Said risk of progression can be correlated to specific treatments.
  • the present invention also provides a method of determining a treatment regime of an individual having CTCL said method comprising the steps of
  • the CTCL is MF.
  • a high risk of disease progression means that there is a high risk that the disease progresses to an aggressive stage.
  • said individual having a high risk of disease progression has Mycosis fungoides at stage IIB-IVB.
  • the systemic treatment is as defined herein above.
  • said systemic treatment is selected from the group consisting of interferon alpha, bexarotene, methotrexate, corticosteroids, pegylated liposomal doxorubicin, histone deacetylase inhibitors (HDACi) such as eg. vorinostat or romidepsin, alemtuzumab and psoralen plus ultraviolet A light.
  • HDACi histone deacetylase inhibitors
  • the mentioned drugs can be used either alone or in combination with other either topical or systemic treatments.
  • Said individual is as defined herein above.
  • said individual is a human being. Kit
  • kits for determining the risk of disease progression in an individual having CTCL comprising at least one probe or at least one pair of probe that specifically bind to a region of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a
  • said CTCL is MF.
  • said at least one probe or at least one probe set specifically binds to a region of said at least one miRNA under amplification conditions.
  • said kit further comprises a microarray chip, wherein said probe(s) is/are located on said microarray chip.
  • said kit further comprises a QPCR Microfluidic Card.
  • said kit further comprises at least one additional component.
  • the additional component may be used simultaneously or sequentially with other components of the kit.
  • the additional component may in one embodiment be or comprise means for extracting RNA, such as miRNA, from a sample.
  • the additional component is or comprises reagents for performing microarray analysis.
  • the additional component comprises or is reagents for performing quantitative real time polymerase chain reaction (QPCR).
  • the kit may also comprise instructions for use of said kit and/or additional components.
  • FFPE formalin fixed paraffin-embedded
  • stage ⁇ IIB advanced MF
  • stage ⁇ IIB advanced MF
  • stage ⁇ IIB advanced MF
  • patients categorized as having non-progressive disease were followed for at least 5 years since disease onset.
  • the patients were staged according to the ISCL/EORTC proposal (Olsen E et al. Blood 2007; 1 10(6): 1713-22).
  • stage IA-IIA stage IIB-IVB
  • PFS progression free survival
  • OS overall survival
  • biopsies from MF patients in the primary cohort and the biopsies from the healthy controls were collected and processed.
  • the data from these patients were examined and the classifier identified.
  • the RNA extraction and qRT-PCR profiling were performed with identical methods and set-ups for the two cohorts.
  • RNA from the 154 FFPE biopsies from the MF patients and from 20 FFPE biopsies from healthy age- and sex matched controls was isolated. 10 ⁇ tissue sections were used for RNA extraction using the RecoverAII Total Nucleic Acid Isolation Kit
  • RNA quantity and quality were checked by a NanoDrop-1000 spectrophotometer.
  • RNA from the discovery cohort, independent validation cohort and healthy controls was used for qRT-PCR based miRNA profiling covering 384 human miRNAs.
  • 50 ng of total RNA from each sample was reverse transcribed to cDNA using the Universal cDNA synthesis kit (Exiqon Vedbaek, Denmark).
  • cDNA was diluted 100 times and ExiLENT SYRR ® Green master mix were transferred to qPCR panels preloaded with primers, using a pipetting robot.
  • Amplification was performed in a Roche LightCycler 480 Real-Time PCR System (Roche). Raw Cp values and melting points were detected using the Roche LC software and exported.
  • ROC receiver operating characteristics
  • the clinical characteristics of the discovery cohort and the independent validation cohort are shown in Table 1 .
  • the median follow-up time was 8.5 years (interquartile range (IQR): 4.9-12.3 years); 9.1 years (IQR: 4.4-13.5 years) for the discovery cohort and 8.0 years (IQR: 5.8-1 1.4 years) for the validation cohort.
  • IQR interquartile range
  • IQR 4.4-13.5 years
  • IQR 5.8-1 1.4 years
  • a risk score formula was derived to calculate a risk score for each patient based on the expression level of the three miRNAs: miR-106b-5p * 0.273 + miR-148a-3p * 0.177 + miR-338-3p * 0.012.
  • the optimum cutoff level was set to 1 .44, so that the number of high-risk individuals in the discovery cohort matched the number of individuals who progressed.
  • Patients with a risk score above 1 .44 were included in the high risk group and risk scores below 1 .44 categorized the patients into the low risk group, Figure 3A.
  • Figure 3A When we assessed the distribution of risk score according to disease progression, patients with a high risk score had generally a higher risk of disease progression, Figure 3A.
  • the five-year progression free survival was 50.0% (95% CI 25% - 100%) in the high risk group and 77.1 % (95% CI 67.2% - 88.4%) in the low risk group.
  • the three-miRNA classifier was a stronger predictor of disease progression than the miRNAs individually, and that it was significantly stronger than existing clinical prognostic factors including sex, age, patch/plaque T-stage (T1 a/T2a vs T1 b/T2b) and the CLIPi score,.
  • CLIPi cutaneous lymphoma international prognostic index.
  • CLIPi group 1 low risk (0-1 risk factors)
  • CLIPi group 2 intermediate risk (2 risk factors)
  • CLIPi group 3 high risk (3-5 risk factors) (Ref: Benton EC et al Eur J Cancer.
  • miRNA id HR pr unit (95% CI) BH adjusted p-value hsa.miR.106b.5p 2,40 (1.72-3.33) 0.000001
  • miRNA id MF HC mean Fold t-test BH
  • MF mycosis fungoides
  • HC lealthy control
  • 3H corr Benjamini-Hoc
  • miRNA HR per unit p- HR per unit p- HR (per unit p- HR per unit p- id (95% CI) valu 95% CI) value (95% CI) value
  • HR hazard ratio
  • CI confidence interval
  • CLIPi cutaneous lymphoma international prognostic index

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Abstract

The present invention relates to methods of prognosing cutaneous T-cell lymphoma in an individual comprising determining the expression level of at least one miRNA selected from a group consisting of identified miRNAs; methods of determining a treatment regime of an individual having T-cell lymphoma by determining the expression level of at least one of said miRNA's; and a kit comprising at least one probe or at least one pair of probe that specifically bind to a region of at least one of said miRNA's.

Description

miRNA's for prognosing cutaneous T-cell lymphoma
Technical field
The present invention relates to methods of prognosing cutaneous T-cell lymphoma in an individual comprising determining the expression level of at least one miRNA selected from a group consisting of identified miRNAs; methods of determining a treatment regime of an individual having primary cutaneous T-cell lymphoma by determining the expression level of at least one of said miRNA's; and a kit comprising at least one probe or at least one pair of probe that specifically bind to a region of at least one of said miRNA's.
Background
Mycosis fungoides (MF) is the most frequent clinical form of cutaneous T-cell lymphomas (CTCL) (Girardi M et al. The New England journal of medicine 2004; 350(19): 1978-88). The majority of patients with MF is diagnosed in the early stages of the disease and is in general expected to have an indolent clinical cause (Agar NS et al. Journal of clinical oncology: official journal of the American Society of Clinical Oncology 2010; 28(31 ): 4730-9). However, the mortality is largest within the first 5 years after the MF diagnosis, indicating that MF both exists in an aggressive and an indolent form (Lindahl LM, et al. Journal of the American Academy of Dermatology 2014 Sep;71 (3):529-35). The aggressive form may account for patients who progress from the early to the advanced stages of MF during their disease cause and for patients having advanced disease at time of diagnosis. The mortality increases in the advanced disease stages and require aggressive treatment. It remains a challenge at time of diagnosis to identify patients, who will progress from the early to the advanced stages of MF during their disease cause and have a worsened prognosis. Existing clinical practice is to monitor the patient clinically and upon disease progression more aggressive treatment is initiated. Thus, the clinical treatment guidelines provide recommendations according to the clinical stage of the disease (Trautinger F et al. European journal of cancer 2006; 42(8): 1014-30). Other predictive factors for progression and prognosis have not yet been integrated in the treatment
recommendations. A need for predictive stratification of patients with early stage MF according to their risk of disease progression and prediction of survival is therefore obvious. Recently, the cutaneous lymphoma international prognostic index (CLIPi) was developed as a prognostic tool for early MF or advanced MF and Sezary syndrome (SS) (Benton EC et al. European journal of cancer 2013; 49(13): 2859-68). CLIPi is based on clinical variables that in a multivariable analysis on a large cohort of MF and SS patients were associated with an increased risk of disease progression and/or reduced survival (Agar NS et al. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2010; 28(31 ): 4730-9). Moreover, several genomic and epigenetic alterations have been proposed to have a possible role as prognostic markers, but no molecular prognostic classifiers have been developed for patients with MF. In solid cancers e.g. colon cancer clinical prognostic factors have been significantly improved by adding a prognostic miRNA classifier (Zhang JX et al. The Lancet Oncology 2013; 14(13): 1295-306). Molecular studies within MF are usually based on small patient cohorts due to the rarity of the disease. Consequently, despite of an urgent need of prognostic biomarkers for patients with MF, such markers have not yet been developed.
Summary
Efforts to make possible an early diagnosis of CTCL such as MF are urgently needed, in order to improve the outcome of existing therapies.
To overcome this challenge the inventors of the present invention have developed a molecular prognostic classifier for patients having CTCL or MF at an early stage.
Based on biopsies from patients diagnosed with early stage MF the inventors of the present invention have developed a miRNA prognostic classifier that may add substantial improvement of the existing clinical prognostic predictors in patients with early stage CTCL such as MF.
In one aspect the present invention provides a method of prognosing cutaneous T-cell lymphoma in an individual, said method comprising:
i. providing a test sample from said individual;
ii. determining the expression level of at least one miRNA in said test sample, wherein the at least one miRNA is selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p
Preferably said prognosing includes determing the risk of disease progression. In a preferred embodiment said disease progression means that the stage of Mycosis fungoides progresses to stage IIB-IVB.
In a preferred embodiment the present invention provides a method of determining whether an individual is at risk of developing an aggressive form of cutaneous T-cell lymphoma (CTCL), said method comprising:
i. providing a test sample from said individual;
ii. determining the expression level of at least one miRNA in said test sample, wherein the at least one miRNA is selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p. It is preferred that said individual has CTCL or is diagnosed with CTCL. The term individual may be used interchangeably with patient. Preferably, the individual is a human being. In a preferred embodiment said CTCL is MF. In one embodiment said test sample comprises tissue cells. Preferably said tissue cells are obtained from a
In one embodiment the method according to the present invention comprises determining the expression levels of at least two miRNA's. In another embodiment the method comprises determining the expression levels of at least three miRNAs. In yet another embodiment the method comprises determining the expression levels of at least 4, such as at least 5, at least 6, at least 7, at least 8, at least 9 or such as at least 10 miRNA's. In one embodiment the method according to the present invention comprises determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p. In another embodiment the method comprises determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p and miR-148a-3p. In yet another embodiment the method comprises determining the expression level of at least two miRNA's selected from the group consisting of miR-106b-5p, miR-148a-3p and miR- 338-3p. In a particular embodiment the method comprises determining the expression level of miR-106b-5p and miR-148a-3p. In another particular embodiment the method comprises determining the expression level of miR-106b-5p, miR-148a-3p and miR- 338-3p.
In one embodiment said individual has Mycosis fungoides (MF) at an early stage. Preferably, said early stage is stage IA-IIA. In one embodiment of the present invention the risk of disease progression. in said individual is determined by calculating a risk score R. Preferably, the risk score R is a linear combination of one or more normalised Cp levels of one or more miRNAs. In a preferred embodiment R is calculated using the formula:
R= βι * Cpi + β2 * Cp2 + ....+ βη-1 * Cpn-1 + βη * Cpn.
wherein Cpi ...Cpn refers to the normalized crossing point value for a given miRNA, wherein β-ι,.. βη are coefficients calculated by linear regression and wherein n is an integer and refers to the number of miRNA tested.
In one embodiment of the present invention an individual having a high or an increased risk of disease progression is subjected to systemic treatment. For example, said systemic treatment can be selected from the group consisting of interferon alpha, bexarotene, methotrexate, corticosteroids, pegylated liposomal doxorubicin, histone deacetylase inhibitors (HDACi) such as eg. vorinostat or romidepsin, alemtuzumab and psoralen plus ultraviolet A light.
It is preferred that said individual is a human being. In one embodiment of the present invention said level(s) of miRNA is/are determined by amplifying a portion of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21.3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p,
miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
In another embodiment of the present invention said level(s) of miRNA is/are determined using an oligonucleotide probe capable of binding to the amplified portion of said at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21.3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p,
miR.18a.5p, miR.532.5p and miR.192.5p.
A second aspect of the present invention relates to a method of determining a treatment regime of an individual having cutaneous T-cell lymphoma said method comprising the steps of
i. determining the risk of disease progression in an individual by the method as defined in anyone of the preceding claims
ii. selecting individuals having a high risk of disease progression
iii. subjecting said individual to systemic treatment.
Preferably, said individual having a high risk of disease progression has Mycosis fungoides at stage IIB-IVB. Said systemic treatment may for example be selected from the group consisting of interferon alpha, bexarotene, methotrexate, corticosteroids, pegylated liposomal doxorubicin, histone deacetylase inhibitors (HDACi) such as eg. vorinostat or romidepsin, alemtuzumab and psoralen plus ultraviolet A light.
It is preferred that said individual is a human being.
A third aspect of the present invention relates to a kit for determining the risk of disease progression in an individual having cutaneous T-cell lymphoma, said kit comprising at least one probe or at least one pair of probe that specifically bind to a region of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21.3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p. In a preferred embodiment said at least one probe or at least one pair of probe specifically bind to a region of said at least one miRNA under amplification conditions.
In an embodiment said kit further comprises a microarray chip, wherein said probe(s) is/are located on said microarray chip.
In another embodiment said kit further comprises a QPCR Microfluidic Card.
In yet another embodiment said kit further comprises at least one additional component. For example said additional component comprises means for extracting RNA, such as miRNA, from a sample. In another embodiment said additional component comprises reagents for performing microarray analysis. In a further embodiment said additional component comprises reagents for performing QPCR analysis.
Description of Drawings
Figure 1. 1A: Hierarchical clustering of the 82 mycosis fungoides patients in the discovery cohort compared with the 20 age- and sex matched healthy controls. 1 B: LASSO coefficient profiles of the strongest disease-related miRNAs to predict disease progression.
Figure 2. Leave-one-out cross validation for turning parameter selection in the LASSO model for the three miRNAs. The partial likelihood deviance is plottet against the LASSO tuning parameter, lambda. The shaded band indicate the standard error (SE) of the partial likelihood deviance. The vertical dotted line indicate the lambda value with the minimum error and the dashed line indicate the largest lambda value where the deviance is within one SE of the minimum. We use the latter criteria to select lambda=0.158. Using this value of lambda there are three miRs that have non-zero coefficients in the model.
Figure 3. Risk score by the three-miRNA classifier, time dependent ROC curves and Kaplan-Meier progression free survival curves in the discovery cohort and the validation cohort. Risk score, time dependent ROC curve and progression free survival curves for the discovery cohort (A-C) and the validation cohort (D-F). The area under the curve (AUC) was calculated for the ROC curves to assess prognostic accuracy.
Figure 4. Progression free survival curves for all 154 patients with early stage MF based on the three-miRNA classifier stratified by clinical prognostic factors and clinical characteristics. Treatment is defined by use of skin-directed therapies (topical corticosteroids, phototherapy or nitrogen mustard) upon diagnosis. No patients received systemic therapies. CLIPi was categorised as CLIPi<3, including patients with CLIPi group 1 = low risk (0-1 risk factors) and CLIPi group 2= intermediate risk (2 risk factors); and CLI Pi=3, including patients with CLIPi group 3= high risk (3-5 risk factors). (Benton EC et al. European Journal of Cancer. 2013;49(13):2859-2868.).
Figure 5. Accuracy of the three-miRNA classifier, clinical prognostic factors and single miRNAs from the classifier by time-dependent ROC curves of progression free survival. (A) Comparisons of the prognostic accuracy of the three-miRNA classifier and existing clinical prognostic factors: sex, age, T1 b or T2b, clinical stage and CLIPi. (B)
Comparisons of the prognostic accuracy of the three-miRNA-based classifier and the single miRNAs: miR-106b-5p, miR-148a-3p and miR-338-3p Figure 6. Proportion of overall survival in the high and low risk group of disease progression in patients with early stage mycosis fungoides predicted by the three- miRNA classifier.
Figure 7. Time to progression for each individual patient. The horizontal line illustrates 5 years after diagnosis; 42 patients (82%) progressed within the first 5 years after their diagnosis.
Detailed description Definitions
The term "amplification" as used herein refers to the process wherein a plurality of exact copies of one or more gene loci or gene portions (template) is synthesised. In one preferred embodiment of the present invention, amplification of a template comprises the process wherein a template is copied by a nucleic acid polymerase or polymerase homologue, for example a DNA polymerase or an RNA polymerase. For example, templates may be amplified using reverse transcription, the polymerase chain reaction (PCR), ligase chain reaction (LCR), in vivo amplification of cloned DNA, isothermal amplification techniques, and other similar procedures capable of generating a complementing nucleic acid sequence.
A 'probe' as used herein refers to a hybridization probe. A hybridization probe is a (single-stranded) fragment of DNA or RNA of variable length (usually 20-1000 bases long), which is used in DNA or RNA samples to detect the presence of nucleotide sequences (the DNA target) that are complementary to the 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. To detect hybridization of the probe to its target sequence, the probe is tagged (or labelled) with a molecular marker of either radioactive or fluorescent molecules. DNA sequences or RNA transcripts that have moderate to high sequence similarity to the probe are then detected by visualizing the hybridized probe.
Hybridization probes used in DNA microarrays refer to DNA covalently attached to an inert surface, such as coated glass slides or gene chips, and to which a mobile cDNA target is hybridized. A double stranded nucleic acid contains two strands that are complementary in sequence and capable of hybridizing to one another. In general, a gene is defined in terms of its coding strand, but in the context of the present invention, an oligonucleotide primer, which hybridize to a gene as defined by the sequence of its coding strand, also comprise oligonucleotide primers, which hybridize to the complement thereof.
The term "nucleotide" as used herein defines a monomer of RNA or DNA. A nucleotide is a ribose or a deoxyribose ring attached to both a base and a phosphate group. Both mono-, di-, and tri-phosphate nucleosides are referred to as nucleotides. The term "oligonucleotide" as used herein refers to oligonucleotides of both natural and/or non-natural nucleotides, including any combination thereof. The natural and/or non-natural nucleotides may be linked by natural phosphodiester bonds or by non- natural bonds. Preferred oligonucleotides comprise only natural nucleotides linked by phosphodiester bonds. The oligomer or polymer sequences of the present invention are formed from the chemical or enzymatic addition of monomer subunits. The term "oligonucleotide" as used herein includes linear oligomers of natural or modified monomers or linkages, including deoxyribonucleotides, ribonucleotides, anomeric forms thereof, peptide nucleic acid monomers (PNAs), locked nucleotide acid monomers (LNA), and the like, capable of specifically binding to a single stranded polynucleotide tag by way of a regular pattern of monomer-to-monomer interactions, such as Watson-Crick type of base pairing, base stacking, Hoogsteen or reverse Hoogsteen types of base pairing, or the like. Usually monomers are linked by phosphodiester bonds or analogs thereof to form oligonucleotides ranging in size from a few monomeric units, e.g. 3-4, to several tens of monomeric units, e.g. 40-60.
Whenever an oligonucleotide is represented by a sequence of letters, such as
"ATGCCTG," it will be understood that the nucleotides are in 5'→ 3' order from left to right and the "A" denotes deoxyadenosine, "C" denotes deoxycytidine, "G" denotes deoxyguanosine, and "T" denotes thymidine, unless otherwise noted. When a double stranded DNA molecule is shown, the nucleotides of the top strand are in 5'→ 3' order from left to right and the nucleotides of the bottom strand are then in 3'→ 5' order from left to right. Usually, oligonucleotides of the invention comprise the four natural nucleotides; however, they may also comprise methylated or non-natural nucleotide analogs. As used herein, "nucleic acid" or "nucleic acid molecule" refers to polynucleotides, such as deoxyribonucleic acid (DNA) or ribonucleic acid (RNA), oligonucleotides, fragments generated by the polymerase chain reaction (PCR), and fragments generated by any of ligation, scission, endonuclease action, and exonuclease action. Nucleic acid molecules can be composed of monomers that are naturally-occurring nucleotides (such as DNA and RNA), or analogs of naturally-occurring nucleotides (e.g. alpha- enantiomeric forms of naturally-occurring nucleotides), or a combination of both.
Modified nucleotides can have alterations in sugar moieties and/or in pyrimidine or purine base moieties. Sugar modifications include, for example, replacement of one or more hydroxyl groups with halogens, alkyl groups, amines, and azido groups, or sugars can be functionalized as ethers or esters. Moreover, the entire sugar moiety can be replaced with sterically and electronically similar structures, such as aza-sugars and carbocyclic sugar analogs. Examples of modifications in a base moiety include alkylated purines and pyrimidines, acylated purines or pyrimidines, or other well-known heterocyclic substitutes. Nucleic acid monomers can be linked by phosphodiester bonds or analogs of such linkages. Analogs of phosphodiester linkages include phosphorothioate, phosphorodithioate, phosphoroselenoate, phosphorodiselenoate, phosphoroanilothioate, phosphoranilidate, phosphoramidate, and the like. The term "nucleic acid molecule" also includes e.g. so-called "peptide nucleic acids," which comprise naturally-occurring or modified nucleic acid bases attached to a polyamide backbone. Nucleic acids can be either single stranded or double stranded. In an aspect of the present invention, 'nucleic acid' is meant to comprise antisense oligonucleotides (ASO), small inhibitory RNAs (siRNA), short hairpin RNA (shRNA) and microRNA (miRNA). The term "microRNA" or "miRNA" or "miR" as used herein refers to is a small non- coding RNA molecule. MicroRNAs (miRNA) are single-stranded RNA molecules of about 19-25 nucleotides in length, which regulate gene expression. miRNAs are either expressed from non-protein-coding transcripts or mostly expressed from protein coding transcripts. They are processed from primary transcripts known as pri-miRNA to shorter stem-loop structures called pre-miRNA and finally to functional mature miRNA. Mature miRNA molecules are partially complementary to one or more messenger RNA (mRNA) molecules, and their main function is to inhibit gene expression. This may occur by preventing mRNA translation or increasing mRNA turnover/degradation. The transcripts encoding miRNAs are much longer than the processed mature miRNA molecule; miRNAs are first transcribed as primary transcripts or pri-miRNA with a cap and poly-A tail by RNA polymerase II and processed to short, 70-nucleotide stem-loop structures known as pre-miRNA in the cell nucleus. This processing is performed in animals (including humans) by a protein complex known as the Microprocessor complex, consisting of the ribonuclease III Drosha and the double-stranded RNA binding protein Pasha. These pre-miRNAs are then exported to the cytoplasm by Exportin-5/Ran-GTP and processed to mature miRNAs by interaction with the ribonuclease III Dicer and separation of the miRNA duplexes. The mature single- stranded miRNA is incorporated into a RNA-induced silencing complex (RlSC)-like ribonucleoprotein particle (miRNP). The RISC complex is responsible for the gene silencing observed due to miRNA expression and RNA interference. The pathway is different for miRNAs derived from intronic stem-loops; these are processed by Dicer but not by Drosha. When Dicer cleaves the pre-miRNA stem-loop, two complementary short RNA molecules are formed, but only one is integrated into the RISC complex. This strand is known as the guide strand and is selected by the argonaute protein, the catalytically active RNase in the RISC complex, on the basis of the stability of the 5' end. The remaining strand, known as the anti-guide or passenger strand, is degraded as a RISC complex substrate. After integration into the active RISC complex, miRNAs base pair with their complementary mRNA molecules. This may induce mRNA degradation by argonaute proteins, the catalytically active members of the RISC complex, or it may inhibit mRNA translation into proteins without mRNA degradation.
The function of miRNAs appears to be mainly in gene regulation. For that purpose, a miRNA is (partly) complementary to a part of one or more mRNAs. Animal (including human) miRNAs are usually complementary to a site in the 3' UTR. The annealing of the miRNA to the mRNA then inhibits protein translation, and sometimes facilitates cleavage of the mRNA (depending on the degree of complementarity). In such cases, the formation of the double-stranded RNA through the binding of the miRNA to mRNA inhibits the mRNA transcript through a process similar to RNA interference (RNAi). Further, miRNAs may regulate gene expression post-transcriptionally at the level of translational inhibition at P-bodies. These are regions within the cytoplasm consisting of many enzymes involved in mRNA turnover; P bodies are likely the site of miRNA action, as miRNA-targeted mRNAs are recruited to P bodies and degraded or sequestered from the translational machinery. In other cases it is believed that the miRNA complex blocks the protein translation machinery or otherwise prevents protein translation without causing the mRNA to be degraded. miRNAs may also target methylation of genomic sites which correspond to targeted mRNAs. miRNAs function in association with a complement of proteins collectively termed the miRNP (miRNA ribonucleoprotein complex).
Under a standard nomenclature system, miRNA names are assigned to experimentally confirmed miRNAs before publication of their discovery. The prefix "mir" is followed by a dash and a number, the latter often indicating order of naming. For example, mir-123 was named and likely discovered prior to mir-456. The uncapitalized "mir-" refers to the pre-miRNA, while a capitalized "miR-" refers to the mature form. miRNAs with nearly identical sequences bar one or two nucleotides are annotated with an additional lower case letter. For example, miR-123a would be closely related to miR-123b. miRNAs that are 100% identical but are encoded at different places in the genome are indicated with additional dash-number suffix: miR-123-1 and miR-123-2 are identical but are produced from different pre-miRNAs. Species of origin is designated with a three-letter prefix, e.g., hsa-miR-123 would be from human (Homo sapiens) and oar-miR-123 would be a sheep (Ovis aries) miRNA. Other common prefixes include V for viral (miRNA encoded by a viral genome) and 'd' for Drosophila miRNA. microRNAs originating from the 3' or 5' end of a pre-miRNA are denoted with a -3p or -5p suffix. (In the past, this distinction was also made with 's' (sense) and 'as' (antisense)).
An asterisk following the name indicates that the miRNA is an anti-miRNA to the miRNA without an asterisk (e.g. miR-123* is an anti-miRNA to miR-123).
As used herein, it is understood that 'miR-' and 'hsa-miR' is used interchangeably; the results of the present invention are obtained from human samples and human miRNAs are examined. Also, it is understood that e.g. hsa-miR-123 is identical to miR-123, and that this may also be denoted miR.123 as well as miR-123 or hsa-miR-123 or hsa.miR.123.
In a few cases the term "let" is used instead of "miR" in the nomenclature, such as for example hsa.let.7i.5p. These microRNAs were identified before the standard nomenclature system was introduced.
miRBase is the central online repository for microRNA (miRNA) nomenclature, sequence data, annotation and target prediction, and may be accessed via
http://www.mirbase.org/. The miRNA names used herein throughout can be accessed via this link, and specifics retrieved. See also Griffiths-Jones et al, "miRBase: tools for microRNA genomics", Nucleic Acids Research, 2008, Vol. 36, Database issue D154- D158. As used herein the terms such as for example miR-106b-5p, miR-125a, miR-148a-3p and miR.92a-3p refer to the human miR sequences found in miR registry database release 12.0 or later and hosted by Sanger Institute, UKas. All miRs are human miR sequences commonly referred to by the prefix "hsa-", e.g. hsa-miR-125a refer to the human miR- 125a. Cutaneous T cell lymphoma (CTCL) is a class of non-Hodgkin lymphoma, which is a type of cancer of the immune system. Unlike most non-Hodgkin lymphomas, CTCL is caused by a mutation of T cells. The malignant T cells in the body initially migrate to the skin, causing various lesions to appear. These lesions change shape as the disease progresses, typically beginning as what appears to be a rash which can be very itchy and eventually forming plaques and tumors before metastasizing to other parts of the body. CTCL is divided into different stages. The stage of CTCL describes how much of the skin is affected , whether formation of a tumor has occured and whether it has spread anywhere else. Usually, CTCL develops very slowly. In the indolent form of CTCL, the symptoms can remain the same for many years and most people never progress beyond the first stage. Occasionally, some people don't experience the early stages of CTCL and their first symptoms may be tumours (raised lumps) on the skin.
The stages of CTCL are described below:
Stage 1 : There are red patches and/or raised red patches (plaques) on the skin. This stage is sometimes divided into:
· Stage 1 A - less than 10% of the skin is affected.
• Stage 1 B - 10% or more of the skin surface is affected.
Stage 2A: Skin symptoms are the same as in stage 1. Some lymph nodes are enlarged, but the lymphoma cells have not spread there.
Stage 2B: There may be one or more tumours on the skin. The lymph nodes may or may not be affected.
Stage 3: More than 80% of the skin is red (erythroderma). The lymph nodes may or may not be affected.
Stage 4: There may be any of the skin symptoms described in the previous stages. The lymphoma has spread to other organs in the body such as the liver. Lymphoma cells may or may not have spread to the lymph nodes and/or blood.
Mycosis fungoides (MF) is the most common type of CTCL, accounting for more than half of all CTCLs. The disease looks different in each patient, with skin symptoms that can appear as patches, plaques, or tumors. Patches are usually flat, possibly scaly, and look like a rash; plaques are thicker, raised, usually itchy lesions that are often mistaken for eczema, psoriasis, or dermatitis; and tumors are raised bumps, which may or may not ulcerate. It is possible to have more than one type of lesion.
A medical history, physical exam, and skin biopsy are important for diagnosis. A physician will examine lymph nodes, order various blood tests, and may conduct other screening tests, such as a chest x-ray or a computed axial tomography (CAT) scan. Scans are usually not needed for those with the earliest stages of the disease.
Mycosis fungoides is difficult to diagnose in its early stages because the symptoms and skin biopsy findings are similar to those of other skin conditions.
Prognostic miRNA biomarkers of the present invention
In one aspect the present invention provides a method of prognosing cutaneous T-cell lymphoma in an individual, said method comprising:
iii. providing a test sample from said individual;
iv. determining the expression level of at least one miRNA in said test sample, wherein the at least one miRNA is selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p
Preferablt said prognosing includes determing the risk of disease progression.
In a preferred embodiment the present invention provides a method of determining whether an individual is at risk of developing an aggressive form of cutaneous T-cell lymphoma (CTCL), said method comprising: iii. providing a test sample from said individual;
iv. determining the expression level of at least one miRNA in said test sample, wherein the at least one miRNA is selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p. It is preferred that said individual has CTCL or is diagnosed with CTCL. The term individual may be used interchangeably with patient. Preferably, the individual is a human being. In a preferred embodiment said CTCL is MF.
It is contemplated that the expression level of at least one of said miRNAs in one embodiment is measured in a sample, such as a tissue sample, from an individual, and said miRNA expression level as compared to a control or baseline level is then associated with the risk of disease progression in an individual having cutaneous T-cell lymphoma. In one embodiment, said miRNAs are used in combination; i.e. the expression level of at least the two miRNAs according to the method above are both used in combination to prognose cutaneous T-cell lymphoma and/or to determine whether an individual is at risk of developing an aggressive form of cutaneous T-cell lymphoma. Thus, the present invention provides a method for distinguishing aggressive forms of cutaneous T-cell lymphoma from non-aggressive form. The method can thus be used to divide the individual or the patient into two groups: a first group having an increased risk of developing an aggressive form of cutaneous T-cell lymphoma and a second group decreased risk of developing an aggressive form of cutaneous T-cell lymphoma. Thus, in one preferred embodiment the method of the present invention comprises determining the expression levels of at least two miRNA's selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
In another preferred embodiment the method as defined herein comprises determining the expression levels of at least three miRNA's selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p,
miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p. In yet another embodiment the method as defined herein comprises determining the expression levels of at least 4, such as at least 5, at least 6, at least 7, at least 8, at least 9 or such as at least 10 miRNA's selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p,
miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
In a further embodiment the method as defined herein comprises determining the expression levels of at least 1 1 , such as at least 12, at least 13, at least 14, at least 15, or such as at least 20 miRNA's selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p,
miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p,
miR.18a.5p, miR.532.5p and miR.192.5p.
In one preferred embodiment the method of the present invention comprises determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p. In another preferred embodiment the method of the present invention comprises determining the expression level of at least two miRNA's selected from the group consisting of miR-106b-5p, miR- 148a-3p and miR-338-3p. In yet another preferred embodiment the method comprises determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p and miR-148a-3p.
In a particular embodiment the method comprises determining the expression level of miR-106b-5p and miR-148a-3p. In another particular embodiment method comprises determining the expression level of miR-106b-5p, miR-148a-3p and miR-338-3p. The embodiments defined above may be combined with determining the expressions level of additional miRNA's as defined above. Thus, in an embodiment the method defined herein comprises determining the expression levels of at least one miRNA selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNA's selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p,
miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p. In another embodiment the method comprises determining the expression levels of at least two miRNA selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNAs selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p,
miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
In yet another embodiment the method comprises determining the expression levels of miR-106b-5p, miR-148a-3p and miR-338-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNAs selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p. In a further embodiment the method defined herein comprises determining the expression levels of at least one miRNA selected from the group consisting of miR- 106b-5p and miR-148a-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNA's selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101 .3p, miR.22.3p,
miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR-338-3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p. In another embodiment the method defined herein comprises determining the expression levels of miR-106b-5p and miR-148a-3p and at least one, such as at least two, at least three, at least 4, at least 5 or such as at least 10 miRNA's selected from the group consisting of miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR-338-3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p,
miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p,
miR.18a.5p, miR.532.5p and miR.192.5p.
Control sample A biomarker, such as a miRNA biomarker, may be correlated to a certain condition based on differences in miRNA expression levels between a sample and a control. If a certain miRNA biomarker is found to be altered in a sample as compared to a (normal) control level, the sample has a certain probability of being associated with a certain condition. Thus, it may be the relationship between the expression levels of two or more biomarkers that is telling of a particular condition; i.e. the relative difference in expression levels between two biomarkers.
In one embodiment, said method further comprises a step of correlating the miRNA expression level(s) as defined herein to a predetermined control level.
The expression of any given miRNA biomarker of the present invention may in one embodiment be either increased or decreased in a sample from an individual or a patient with CTCL such as MF as compared to a control sample.
Thus, in one embodiment, the method according to the present invention further comprises comparing the expression level of at least one miRNA as defined herein in the test sample to the expression level of the corresponding miRNA in a control sample. Hence, the method of the present invention may in one embodiment comprise comparing the expression levels of the specific combinations of miRNAs as defined herein in the test sample to the expression levels of the corresponding miRNAs in a control sample.
In one embodiment, the expression level(s) of at least one, at least two, at least three, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9 or at least 10 miRNA(s) selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p is/are altered as compared to the expression level(s) of the corresponding miRNA(s) in a control sample.
In one embodiment expression levels of one or more of the miRNAs as defined in the embodiments herein above is/are altered as compared to the expression level(s) of the corresponding miRNA(s) in a control sample. It is contemplated that a difference in the expression levels of said at least one miRNA in the test sample and in the control sample is indicative of disease progression or that said individual has an increased risk of developing an aggressive form of CTCL.
Preferably, said control sample is obtained from a healthy individual or from an individual not having CTCL. In a preferred embodiment the control sample comprises tissue cells. Preferably, the control sample is a tissue sample. Individual
The present invention relates to a method of prognosing CTCL in an individual. Thus, is contemplated that the individual has CTCL or is diagnosed with CTCL. Preferably, said individual has CTCL at an early stage. In a preferred embodiment said individual has MF, preferably MF at an early stage. It is preferred that said early stage is stage IA-IIA.
The term "Individual" refers to vertebrates, particular members of the mammalian species, preferably primates including humans. In a preferred embodiment said individual is a human being. As used herein, 'subject', 'individual' and "patient" may be used interchangeably.
Samples
The test sample according to the present invention is extracted from an individual and used for miRNA profiling for the subsequent prognosis of CTCL. Thus, the test sample is obtained from an individual having CTCL. The control sample is preferably obtained from a healthy individual or an individual not having CTCL.
The individual may be any animal, such as a mammal, including human beings. In a preferred embodiment, the individual is a human being.
The test sample and/or the control sample can be a body fluid sample such as a blood sample, a urine sample, a faecal sample, a serum sample or a saliva sample. The sample may also be obtained by a skin swabs, nasal swabs or cheek epithelium swabs. In one preferred embodiment the sample is a skin biopsy or a lymph node biopsy. The biopsy may be a small sample of tissue that is taken with a needle or minor surgery. In a preferred embodiment the test sample is a biopsy of the affected skin or the skin tumour. The doctor may for example shave off a thin slice of affected skin, for example where rash or tumour has appeared.
In a preferred embodiment the sample comprises tissue cells. Preferably, the sample is a tissue sample.
Preferably the test sample and the control sample are obtained in the same way. Thus, in a preferred embodiment the control sample and the test sample comprise tissue cells or are tissue samples or more preferably skin biopsies. Several skin sample or biopsies from different areas of the body may be taken.
The tissues or the skin biopsies may be examined under a microscope to determine the stage of CTCL.
The sample extracted from the individual may be analysed essentially immediately, or it may be stored prior to analysis for a variable period of time and at various temperature ranges.
In one embodiment, the sample is stored at a temperature of between -200°C to 37°C, such as between -200 to -100°C, for example -100 to -50°C, such as -50 to -25°C, for example -25 to -10°C, such as -10 to 0°C, for example 0 to 10°C, such as 10 to 20°C, for example 20 to 30°C, such as 30 to 37°C prior to analysis.
In one embodiment, the sample is stored at -20°C and/or -80°C.
In another embodiment, the sample is stored for between 15 minutes and 100 years prior to analysis, such as between 15 minutes and 1 hour, for example 1 to 2 hours, such as 2 to 5 hours, for example 5 to 10 hours, such as 10 to 24 hours, for example 24 hours to 48 hours, such as 48 to 72 hours, for example 72 to 96 hours, such as 4 to 7 days, such as 1 week to 2 weeks, such as 2 to 4 weeks, such as 4 weeks to 1 month, such as 1 month to 2 months, for example 2 to 3 months, such as 3 to 4 months, for example 4 to 5 months, such as 5 to 6 months, for example 6 to 7 months, such as 7 to 8 months, for example 8 to 9 months, such as 9 to 10 months, for example 10 to 1 1 months, such as 1 1 to 12 months, for example 1 year to 2 years, such as 2 to 3 years, for example 3 to 4 years, such as 4 to 5 years, for example 5 to 6 years, such as 6 to 7 years, for example 7 to 8 years, such as 8 to 9 years, for example 9 to 10 years, such as 10 to 20 years, for example 20 to 30 years, such as 30 to 40 years, for example 40 to 50 years, such as 50 to 75 years, for example 75 to 100 years prior to analysis.
In one embodiment, the sample is stored for a few days.
Collection media for sample
A collection media according to the present invention is any media suitable for preserving and/or collecting a sample for immediate or later analysis.
In one embodiment, said collection media is a solution suitable for sample preservation and/or later retrieval of RNA (such as miRNA) from said sample.
In one embodiment, the collection media is an RNA preservation solution or reagent suitable for containing samples without the immediate need for cooling or freezing the sample, while maintaining RNA integrity prior to extraction of RNA (such as miRNA) from the sample. An RNA preservation solution or reagent may also be known as RNA stabilization solution or reagent or RNA recovery media, and may be used
interchangeably herein. The RNA preservation solution may penetrate the harvested cells of the collected sample to retard RNA degradation to a rate dependent on the storage temperature. In a specific embodiment a biopsy sample is obtained from the individual and embedded in paraffin. This sample is preferably stored at room temperature.
The RNA preservation solution may be any commercially available solutions or it may be a solution prepared according to available protocols.
The commercially available RNA preservation solutions may for example be selected from RNAIater® (Ambion and Qiagen), PreservCyt medium (Cytyc Corp),
PrepProtect™ Stabilisation Buffer (Miltenyi Biotec), Allprotect Tissue Reagent (Qiagen) and RNAprotect Cell Reagent (Qiagen). Protocols for preparing a RNA stabilizing solution may be retrieved from the internet (e.g. L.A. Clarke and M.D. Amaral: 'Protocol for RNase-retarding solution for cell samples', provided through The European Working Group on CFTR Expression), or may be produced and/or optimized according to techniques known to the skilled person. In another embodiment, the collection media will penetrate and lyse the cells of the sample immediately, including reagents and methods for isolating RNA (such as miRNA) from a sample that may or may not include the use of a spin column.
Said reagents and methods for isolating RNA (such as miRNA) is described herein below in the section 'analysis of sample'.
Other collection media according to the present invention comprises any media such as water, sterile water, denatured water, saline solutions, formalin, buffers, PBS, TBS, Allprotect Tissue Reagent (Qiagen), cell culture media such as RPMI-1640, DMEM (Dulbecco's Modified Eagle Medium), MEM (Minimal Essential Medium), IMDM (Iscove's Modified Dulbecco's Medium), BGjB (Fitton-Jackson modification), BME (Basal Medium Eagle), Brinster's BMOC-3 Medium, CMRL Medium, C02-Independent Medium, F-10 and F-12 Nutrient Mixture, GMEM (Glasgow Minimum Essential Medium), IMEM (Improved Minimum Essential Medium), Leibovitz's L-15 Medium, McCoy's 5A Medium, MCDB 131 Medium, Medium 199, Opti-MEM, Waymouth's MB 752/1 , Williams' Media E, Tyrode's solution, Belyakov's solution, Hanks' solution and other cell culture media known to the skilled person, tissue preservation media such as HypoThermosol®, CryoStor™ and Steinhardt's medium and other tissue preservation media known to the skilled person.
After the sample is collected, it is subjected to analysis. In one embodiment, the sample is initially used for isolating or extracting RNA according to any conventional methods known in the art; followed by an analysis of the miRNA expression in said sample.
Extraction of RNA
The RNA isolated from the sample may be total RNA, mRNA, microRNA, tRNA, rRNA or any type of RNA. Conventional methods and reagents for isolating RNA from a sample are well known to the skilled person and commercially available. Also, kits for isolating RNA from biopsies embedded in paraffin is commercially available and well known to the skilled person. The RNA may be further amplified, cleaned-up, concentrated, DNase treated, quantified or otherwise analysed or examined such as by agarose gel electrophoresis, absorbance spectrometry or Bioanalyser analysis (Agilent) or subjected to any other post-extraction method known to the skilled person. Microarray analysis
The isolated RNA may be analysed by microarray analysis. In one embodiment, the expression level of one or more miRNAs is determined by the microarray technique.
A microarray is a multiplex technology that consists of an arrayed series of thousands of microscopic spots of DNA oligonucleotides or antisense miRNA probes, called features, each containing picomoles of a specific oligonucleotide sequence. This can be a short section of a gene or other DNA or RNA element that are used as probes to hybridize a DNA or RNA sample (called target) under high-stringency conditions.
Probe-target hybridization is usually detected and quantified by fluorescence-based detection of fluorophore-labeled targets to determine relative abundance of nucleic acid sequences in the target. In standard microarrays, the probes are attached to a solid surface by a covalent bond to a chemical matrix (via epoxy-silane, amino-silane, lysine, polyacrylamide or others). The solid surface can be glass or a silicon chip, in which case they are commonly known as gene chip. DNA arrays are so named because they either measure DNA or use DNA as part of its detection system. The DNA probe may however be a modified DNA structure such as LNA (locked nucleic acid).
In one embodiment, the microarray analysis is used to detect microRNA, known as microRNA or miRNA expression profiling.
The microarray for detection of microRNA may be a microarray platform, wherein the probes of the microarray may be comprised of antisense miRNAs or DNA
oligonucleotides. In the first case, the target is a labelled sense miRNA sequence, and in the latter case the miRNA has been reverse transcribed into cDNA and labelled. The microarray for detection of microRNA may be a commerciaiiy available array platform, such as NCode™ miRNA Microarray Expression Profiling (Invitrogen), miRCURY LNA™ microRNA Arrays (Exiqon), microRNA Array (Agilent), μΡθΓθΑο® Microfluidic Biochip Technology (LC Sciences), MicroRNA Profiling Panels (lllumina), Geniom® Biochips (Febit Inc.), microRNA Array (Oxford Gene Technology), Custom AdmiRNA™ profiling service (Applied Biological Materials Inc.), microRNA Array (Dharmacon - Thermo Scientific), LDA TaqMan analyses (Applied Biosystems), Taqman microRNA Array (Applied Biosystems), Biomark™ HD System (Fluidigm System) using TaqMan reagents or any other commercially available array.
Microarray analysis may comprise all or a subset of the steps of RNA isolation, RNA amplification, reverse transcription, target labelling, hybridisation onto a microarray chip, image analysis and normalisation, and subsequent data analysis; each of these steps may be performed according to a manufacturers protocol.
It follows, that any of the methods as disclosed herein above may further comprise one or more of the steps of:
i) isolating miRNA from a sample,
ii) labelling of said miRNA,
iii) hybridising said labelled miRNA to a microarray or QPCR assay comprising miRNA-specific probes to provide a hybridisation profile for the sample, iv) performing data analysis to obtain a measure of the miRNA expression profile of said sample. another embodiment, the microarray for detection of microRNA is custom made.
A probe or hybridization probe is a fragment of DNA or RNA of variable length, which is used to detect in DNA or RNA samples the presence of nucleotide sequences (the target) that are complementary to the sequence in the probe. One example is a sense miRNA sequence in a sample (target) and an antisense miRNA 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. To detect hybridization of the probe to its target sequence, the probe or the sample is tagged (or labeled) with a molecular marker. Detection of sequences with moderate or high similarity depends on how stringent the hybridization conditions were applied— high stringency, such as high hybridization temperature and low salt in hybridization buffers, permits only hybridization between nucleic acid sequences that are highly similar, whereas low stringency, such as lower temperature and high salt, allows hybridization when the sequences are less similar. Hybridization probes used in microarrays refer to nucleotide sequences covalently attached to an inert surface, such as coated glass slides, and to which a mobile target is hybridized. Depending on the method the probe may be synthesised via phosphoramidite technology or generated by PCR amplification or cloning (older methods). To design probe sequences, a probe design algorithm may be used to ensure maximum specificity (discerning closely related targets), sensitivity (maximum hybridisation intensities) and normalised melting temperatures for uniform hybridisation.
In one embodiment of the present invention said level(s) of miRNA is/are determined by amplifying a portion of one or more of the miRNA(s) as defined in the embodiments herein and above. In one embodiment of the present invention said level(s) of miRNA is/are determined by amplifying a portion of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p. Preferably, said level(s) of miRNA is/are determined using a probe capable of binding to one or more of the miRNA(s) as defined in the embodiments herein and above. For example, said level(s) of miRNA is/are determined using a probe capable of binding to at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
In one embodiment said probe(s) or probe set(s) bind to the amplified portion of said miRNA(s).
In one embodiment 1 to 2 probes or probe set is used per miRNA to be measured, such as 2 to 3 probes, for example 3 to 4 probes, such as 4 to 5 probes, for example 5 to 6 probes, such as 6 to 7 probes, for example 7 to 8 probes, such as 8 to 9 probes or probe sets per miRNA of the present invention to be measured.
In another embodiment, 1 probe or probe set is used for at least one miRNA to be measured, such as 2 probes, for example 3 probes, such as 4 probes, for example 5 probes, such as 6 probes, for example 7 probes, for example 8 probes or probe sets for at least one miRNA of the present invention to be measured.
It follows, that there may be one probe specific to a miRNA to be measured, or more than one probe specific to a miRNA to be measured - which may be called a probe set. Thus, a probe set is a collection of two or more probes designed to interrogate or measure a given sequence.
It is preferred that 1 probe or probe set is used per miRNA to be measured.
RT-QPCR
The isolated RNA may be analysed by quantitative ('real-time') PCR (QPCR). In one embodiment, the expression level of one or more miRNAs is determined by the quantitative polymerase chain reaction (QPCR) technique.
Real-time polymerase chain reaction, also called quantitative polymerase chain reaction (Q-PCR/qPCR/RT-QPCR) or kinetic polymerase chain reaction, is a tech based on the polymerase chain reaction, which is used to amplify and simultaneously quantify a targeted DNA molecule. It enables both detection and quantification (as absolute number of copies or relative amount when normalized to DNA input or additional normalizing genes) of a specific sequence in a DNA sample.
The procedure follows the general principle of polymerase chain reaction; its key feature is that the amplified DNA is quantified as it accumulates in the reaction in real time after each amplification cycle. Two common methods of quantification are the use of fluorescent dyes that intercalate with double-stranded DNA, and modified DNA oligonucleotide probes that fluoresce when hybridized with a complementary DNA.
Frequently, real-time polymerase chain reaction is combined with reverse transcription polymerase chain reaction to quantify low abundance messenger RNA (mRNA), or miRNA, enabling a researcher to quantify relative gene expression at a particular time, or in a particular cell or tissue type.
In a real time PCR assay a positive reaction is detected by accumulation of a fluorescent signal. The Ct (cycle threshold) is defined as the number of cycles required for the fluorescent signal to cross the threshold (i.e. exceeds background level). Ct- values are inversely proportional to the amount of target nucleic acid in the sample (i.e. the lower the Ct-value the greater the amount of target nucleic acid in the sample). Most real time assays undergo 40 cycles of amplification.
Ct-values < 29 are strong positive reactions indicative of abundant target nucleic acid in the sample. Ct-values of 30-37 are positive reactions indicative of moderate amounts of target nucleic acid. Ct-values of 38-40 are weak reactions indicative of minimal amounts of target nucleic acid which could represent an infection state or
environmental contamination.
The QPCR may be performed using chemicals and/or machines from a commercially available platform.
The QPCR may be performed using QPCR machines from any commercially available platform; such as Prism, geneAmp or StepOne Real Time PCR systems (Applied Biosystems), LightCycler (Roche), RapidCycler (Idaho Technology), MasterCycler (Eppendorf), BioMark™ HD System (Fluidigm), iCycler iQ system, Chromo 4 system, CFX, MiniOpticon and Opticon systems (Bio-Rad), SmartCycler system (Cepheid), RotorGene system (Corbett Lifescience), MX3000 and MX3005 systems (Stratagene), DNA Engine Opticon system (Qiagen), Quantica qPCR systems (Techne), InSyte and Syncrom cycler system (BioGene), DT-322 (DNA Technology), Exicycler Notebook Thermal cycler, TL998 System (lanlong), Line-Gene-K systems (Bioer Technology), or any other commercially available platform.
The QPCR may be performed using chemicals from any commercially available platform, such as NCode EXPRESS qPCR or EXPRESS qPCR (Invitrogen), Taqman or SYBR green qPCR systems (Applied Biosystems), Real-Time PCR reagents
(Eurogentec), iTaq mix (Bio-Rad), qPCR mixes and kits (Biosense), and any other chemicals, commercially available or not, known to the skilled person.
The QPCR reagents and detection system may be probe-based, or may be based on chelating a fluorescent chemical into double-stranded oligonucleotides.
The QPCR reaction may be performed in a tube; such as a single tube, a tube strip or a plate, or it may be performed in a microfluidic card in which the relevant probes and/or primers are already integrated.
A Microfluidic card allows high throughput, parallel analysis of mRNA or miRNA expression patterns, and allows for a quick and cost-effective investigation of biological pathways. The microfluidic card may be a piece of plastic that is riddled with micro channels and chambers filled with the probes needed to translate a sample into a diagnosis. A sample in fluid form is injected into one end of the card, and capillary action causes the fluid sample to be distributed into the microchannels. The microfluidic card is then placed in an appropriate device for processing the card and reading the signal. Other analysis methods
The isolated RNA may be analysed by northern blotting. In one embodiment, the expression level of one or more miRNAs is determined by the northern blot technique.
A northern blot is a method used to check for the presence of a RNA sequence in a sample. Northern blotting combines denaturing agarose gel or polyacrylamide gel electrophoresis for size separation of RNA with methods to transfer the size-separated RNA to a filter membrane for probe hybridization. The hybridization probe may be made from DNA or RNA. In yet another embodiment, the isolated RNA is analysed by nuclease protection assay.
The isolated RNA may be analysed by Nuclease protection assay. Nuclease protection assay is a technique used to identify individual RNA molecules in a heterogeneous RNA sample extracted from cells. The technique can identify one or more RNA molecules of known sequence even at low total concentration. The extracted RNA is first mixed with antisense RNA or DNA probes that are
complementary to the sequence or sequences of interest and the complementary strands are hybridized to form double-stranded RNA (or a DNA-RNA hybrid). The mixture is then exposed to ribonucleases that specifically cleave only s/ng/e-stranded RNA but have no activity against double-stranded RNA. When the reaction runs to completion, susceptible RNA regions are degraded to very short oligomers or to individual nucleotides; the surviving RNA fragments are those that were
complementary to the added antisense strand and thus contained the sequence of interest.
Risk score To determine whether a patient or an individual is at risk of developing an aggressive form of cutaneous T-cell lymphoma a risk score R can be calculated.
In one embodiment of the present invention the risk of disease progression in said individual is determined by calculating a risk score R. The risk score R is defined by the following formula:
In one embodiment of the present invention the risk of disease progression in said individual is determined by calculating a risk score R. The risk score R is a linear combination of the normalised Cp levels of different miRNAs: R= βι * Cpi + β2 * Cp2 + β3 * Cp3 + ....+ βη-1 * Cpn-i + βη * Cpn
Where Cp refers to the normalized Cp value for a given miRNA. n is an integer and refers to the number of miRNAs tested. The coefficients, β-ι, βη, are calculated by fitting a multivariate Cox proportional hazards model (Cox DR. Regression models and life tables (with discussion) J R Statist Soc B. 1972;34:187-220.) on progression free survival (PFS): h(t) = ho(t) * exp( βι * Cpi + β2 * Cp2 + β3 * Cp3 + ....+ βη-ι * Cpn-i + βη * Cpn ) where the hazard function h(t) is dependent on the Cp values and h0(t) is a baseline hazard. In the risk score described in the example section the LASSO method was used to shrink the coefficients and reduce the number of variables in the model (Tibshirani R. The lasso method for variable selection in the Cox model. Stat Med. 1997 Feb 28;16(4):385-95).
If for example R is calculated for two miRNAs the formula is as follows:
Figure imgf000035_0001
In one embodiment a cut off value is determined to discriminate patients with high risk and low risk of disease progression. The cutoff can for example be set so that the number of high-risk individuals in the entire cohort matches the number of individuals in the entire cohort who developed disease progression.
An example for calculating a cut off value is disclosed in the example section.
For example, when the risk score is above the cut off value there is a high risk of disease progression. Preferably, disease progression means progression of CTCL such as MF to a more aggressive form. Thus, in a preferred embodiment, said disease progression means that the stage of CTCL or MF progresses to stage IIB-IVB.
An individual having a risk score R above the cut off value may be subjected to intensified surveillance and/or systemic treatment. Systemic treatment may for example include chemotherapy where the individual or the patient is treated with medicines to kill cancer cells. Medicines may for example be put on the skin as a cream or gel. Alternatively, medicines may be taken by mouth or injected into a vein, intramuscularly or subcutaneously so they can reach cancer cells all over the body.
Other types of medicines used for systemic treatment may include retinoids, HDAC inhibitors, corticosteroids, targeted medicine including biological drugs such as but not limited to antibodies or immune therapy. Some of these are applied to the skin. Others are taken by mouth or given as a shot (injection).
In one embodiment the systemic treatment is radiation therapy. Radiation therapy may include X-rays to kill cancer cells and shrink tumors. Total skin electron beam therapy (or TSEBT) may be used to treat skin lymphoma.
In another embodiment the systemic treatment is photodynamic therapy.
Photodynamic therapy uses certain types of UV (ultraviolet) light and medicines called psoralens to kill cancer cells. In yet another embodiment the systemic treatment is Extracorporeal photopheresis (ECP). ECP is used to kill lymphoma cells in the blood. The blood is sent through a machine that exposes it to a special UV (ultraviolet) light. The light kills the lymphoma cells, and the blood is then returned to the body. Method of treatment
According to the present invention, the expression levels of the miRNA biomarkers are correlated with the risk of progression of CTCL, such as the risk of progression to an aggressive stage of CTCL. Said risk of progression can be correlated to specific treatments.
The present invention also provides a method of determining a treatment regime of an individual having CTCL said method comprising the steps of
i. determining the risk of disease progression in an individual by the method as defined in anyone of the preceding claims; ii. selecting individuals having a high risk of disease progression
iii. subjecting said individual to systemic treatment.
In a preferred embodiment the CTCL is MF.
A high risk of disease progression means that there is a high risk that the disease progresses to an aggressive stage. In a preferred embodiment said individual having a high risk of disease progression has Mycosis fungoides at stage IIB-IVB. The systemic treatment is as defined herein above. In one embodiment said systemic treatment is selected from the group consisting of interferon alpha, bexarotene, methotrexate, corticosteroids, pegylated liposomal doxorubicin, histone deacetylase inhibitors (HDACi) such as eg. vorinostat or romidepsin, alemtuzumab and psoralen plus ultraviolet A light. The mentioned drugs can be used either alone or in combination with other either topical or systemic treatments.
Said individual is as defined herein above. Preferably said individual is a human being. Kit
Another aspect of the present invention relates to a kit for determining the risk of disease progression in an individual having CTCL, said kit comprising at least one probe or at least one pair of probe that specifically bind to a region of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
In a preferred embodiment said CTCL is MF. Embodiments and preferred embodiments describing specific combinations of miRNA's are as defined herein above. In one embodiment said at least one probe or at least one probe set specifically binds to a region of said at least one miRNA under amplification conditions.
In one embodiment said kit further comprises a microarray chip, wherein said probe(s) is/are located on said microarray chip.
In another embodiment said kit further comprises a QPCR Microfluidic Card.
In yet another embodiment said kit further comprises at least one additional component. The additional component may be used simultaneously or sequentially with other components of the kit. The additional component may in one embodiment be or comprise means for extracting RNA, such as miRNA, from a sample. In another embodiment the additional component is or comprises reagents for performing microarray analysis. In yet another embodiment the additional component comprises or is reagents for performing quantitative real time polymerase chain reaction (QPCR). The kit may also comprise instructions for use of said kit and/or additional components.
Examples Methods
Patient cohorts
We used 174 formalin fixed paraffin-embedded (FFPE) skin biopsies from 154 patients with early stage MF (stage < MB) and 20 healthy age- and sex matched controls. All patients were identified retrospectively using our Danish nationwide registries and diagnosed in the period 1981 -2013. First, a primary cohort of 82 patients diagnosed with MF in the western part of Denmark was identified and subsequently an
independent validation cohort of 72 patients diagnosed in the eastern part of Denmark was identified. Patients were categorized based on their medical charts and the histopathological descriptions of the biopsy showing the MF diagnosis. The early MF diagnosis was confirmed as defined by clinical findings consistent with MF stage IA-IIA and histopathological findings of infiltrating atypical T-cells, epidermotropism and optionally Pautrier's microabscesses. Thus, the specific biopsy used for the MF diagnosis in each patient was identified. Patients with advanced stage MF at time of diagnosis were excluded. The biopsies were generously lent out from the Departments of Pathology in Denmark. The patients were categorized according to whether their disease progressed to advanced MF (stage≥IIB) or stayed in the early stages during follow-up (stage <IIB). Patients categorized as having non-progressive disease were followed for at least 5 years since disease onset. Moreover, we extracted data from the patient files on clinical characteristics including age, sex, clinical stage, T-stage, the CLIPi risk score for early MF, treatment upon time of diagnosis, date of death and of whether the death were MF related or not. The patients were staged according to the ISCL/EORTC proposal (Olsen E et al. Blood 2007; 1 10(6): 1713-22).
Disease progression was defined as progression from the early stages (stage IA-IIA) to the advanced stages of MF (stage IIB-IVB), which may impact the prognosis (Agar NS, et al. Journal of clinical oncology: official journal of the American Society of Clinical Oncology 2010; 28(31 ): 4730-9). Progression free survival (PFS) was defined as time from diagnosis to progression and/or disease specific death. Overall survival (OS) was defined as time from diagnosis to death from any cause.
Procedures
First, biopsies from MF patients in the primary cohort and the biopsies from the healthy controls were collected and processed. The data from these patients were examined and the classifier identified. Subsequently, we collected and processed the biopsies from the independent validation cohort. The RNA extraction and qRT-PCR profiling were performed with identical methods and set-ups for the two cohorts.
RNA extraction
RNA from the 154 FFPE biopsies from the MF patients and from 20 FFPE biopsies from healthy age- and sex matched controls was isolated. 10 μηη tissue sections were used for RNA extraction using the RecoverAII Total Nucleic Acid Isolation Kit
(ThermoFisher Scientific/Applied Biosystems) according to the manufacture's guidelines. Total RNA quantity and quality were checked by a NanoDrop-1000 spectrophotometer. qRT-PCR miRNA profiling
The extracted RNA from the discovery cohort, independent validation cohort and healthy controls was used for qRT-PCR based miRNA profiling covering 384 human miRNAs. 50 ng of total RNA from each sample was reverse transcribed to cDNA using the Universal cDNA synthesis kit (Exiqon Vedbaek, Denmark). cDNA was diluted 100 times and ExiLENT SYRR®Green master mix were transferred to qPCR panels preloaded with primers, using a pipetting robot. Amplification was performed in a Roche LightCycler 480 Real-Time PCR System (Roche). Raw Cp values and melting points were detected using the Roche LC software and exported. Reactions with several melting points, melting points deviating from assay specifications and amplification efficacy below 1.6 were removed as well as reactions with Cp values >37 or Cp values that were within 5 Cp values of the negative control reaction. All data in each data set were normalized to the average Cp value of assays detected in all samples (global mean), which was identified as the best normalizer using NormFinder.
Statistical analysis
First, we used the entire patient cohort (154 patients) to investigate the predictive single marker effect of all 384 miRNAs using a Cox proportional hazards regression. 45 miRNAs did significantly predict disease progression after correction for multiple testing (Benjamini-Hocberg correction). Next, we developed a method using these miRNAs to identify a prognostic classifier for patients diagnosed with early stage MF.
We assume that the miRNA that are useful for predicting disease progression are related to the disease and thus show differential expression when cases are compared to healthy controls. So we first performed hierarchical clustering analysis, Figure 1 , and compared the miRNA expression in the discovery cohort with the healthy controls. Significantly different expressed miRNAs were identified using a t-test followed by correction for multiple testing (Benjamini-Hocberg correction). Based on these miRNAs we then build a prognostic classifier. To avoid problems with missing data we performed imputation of missing values using the k-nearest-neighbors method implemented in the R library input (Troyanskaya O et al. Bioinformatics 2001 ; 17(6): 520-5). Next, we fitted a Cox's proportional hazards model and used the LASSO method for variable selection and shrinkage. The regularization parameter was chosen as the largest value where the error was within 1 standard error of the minimum as determined by leave-one-out cross-validation. The Cox regression model for PFS that we build using the discovery cohort allowed us to calculate a score for each individual that reflects the risk of disease progression. We divided the individuals into high-risk and low-risk groups by setting a cutoff on this risk score. The cutoff was set so that the number of high-risk individuals in the discovery cohort matched the number of individuals in the discovery cohort that progressed. LASSO Cox regression is a well- established method to select the most predictive markers for time to event analysis with high-throughput data (Tibshirani R. Statistics in medicine 1997; 16(4): 385-95).
We draw time-dependent receiver operating characteristics (ROC) curves to assess the accuracy of the prediction of disease progression for the miRNA classifier and the clinical predictive variables associated with disease outcome.
For PFS and OS analysis, we used the Kaplan-Meier method draw survival curves and we used Cox proportional hazards model to estimate the effect of various covariates. Ethics: The study was approved by the local ethical committee (1 -10-72-91 -13) and the Data Protection Agency (Datatilsynet 1 -16-02-478-15). Results
The clinical characteristics of the discovery cohort and the independent validation cohort are shown in Table 1 . The median follow-up time was 8.5 years (interquartile range (IQR): 4.9-12.3 years); 9.1 years (IQR: 4.4-13.5 years) for the discovery cohort and 8.0 years (IQR: 5.8-1 1.4 years) for the validation cohort. Fifty-one patients (33%) progressed from the early to the advanced stages of MF within a median time of 2.0 years (IQR: 8.4 months - 4.2 years). Among those who progressed, 82% progressed within the first 5 years after diagnosis (Figure 7).
Based on the entire patient cohort (n=154) the predictive single marker effect of all 384 miRNAs was calculated using a Cox proportional hazards regression. We found that 55 of these miRNAs could significantly predict disease progression after correction for multiple testing (Benjamini-Hocberg correction), Table 2. Thus, these miRNAs can predict disease progression and hence be set in different combinations to form a prognostic classifier. The formula for calculating a risk score and cut off value to discriminate patients with a high and low risk of disease progression is mentioned in the section of statistical analysis.
This technique was further used and exemplified. In order to develop a disease related prognostic miRNA classifier, we assessed the miRNA expression in the discovery cohort compared to healthy age and sex matched controls and identified 123 differently expressed miRNAs. 72 miRNAs were upregulated and 51 miRNAs were
down regulated, Table 3. Hierarchical clustering based on these differently expressed miRNAs did successfully separate the 85 MF samples from the 20 healthy control samples, Figure 1A. The univariate analysis of the association between the expression of the 123 miRNAs and PFS are shown in Table 4. Based on the identified differently expressed miRNAs between MF and healthy control samples, we used a LASSO Cox regression model and leave-one-out cross validation to build a classifier to predict proportion of disease progression in patients with early stage MF. Three miRNAs were selected from the 123 identified miRNAs in the discovery cohort: miR-106b-5p, miR- 148a-3p and miR-338-3p, Figure 1 B and Figure 2. A risk score formula was derived to calculate a risk score for each patient based on the expression level of the three miRNAs: miR-106b-5p*0.273 + miR-148a-3p*0.177 + miR-338-3p*0.012. The optimum cutoff level was set to 1 .44, so that the number of high-risk individuals in the discovery cohort matched the number of individuals who progressed. Patients with a risk score above 1 .44 were included in the high risk group and risk scores below 1 .44 categorized the patients into the low risk group, Figure 3A. When we assessed the distribution of risk score according to disease progression, patients with a high risk score had generally a higher risk of disease progression, Figure 3A. The accuracy of the three- miRNA classifier for prediction of PFS was assessed by time-dependent ROC analysis for the entire follow-up period and at varying time-points, Figure 3B. Progression free survival was significantly different in the high risk compared to the low risk group, HR 4.45 (95% CI 2.08-9.54) P= 0.000065, Figure 3C. Five-years progression free survival was 51.4% (95% CI 35.9% - 73.5%) for the high risk group and 85.3% (95% CI 75.7% - 96.1 %) in the low-risk group. Of notice, the distribution of clinical patient characteristics was largely similar in the high risk and low risk group, Table 1.
In order to validate the prognostic value of the three-miRNA classifier, it was applied to an independent validation cohort of 71 diagnostic biopsies from patients with early stage MF. We confirmed that patients with a high risk score had generally a higher risk of disease progression when assessing the distribution of risk score according to disease progression, Figure 3D. ROC curves assessing the prognostic accuracy of the classifier in the independent validation cohort are shown in Figure 3E. Progression free survival curves were significantly different in the high risk compared to the low risk group, HR 4.60 (95% CI 1 .75-12.0), P= 0.006, Figure 3F. The five-year progression free survival was 50.0% (95% CI 25% - 100%) in the high risk group and 77.1 % (95% CI 67.2% - 88.4%) in the low risk group. Performing univariate analysis, we found that the three-miRNA classifier was a stronger predictor of disease progression than the miRNAs individually, and that it was significantly stronger than existing clinical prognostic factors including sex, age, patch/plaque T-stage (T1 a/T2a vs T1 b/T2b) and the CLIPi score,.
Thirty-eight (25%) of all patients received symptomatic topical treatment at the time the diagnostic biopsy was obtained (Table 1 ), 33 patients were treated with topical corticosteroids, 3 patients with UVB and 2 patients with nitrogen mustard. Systemic treatment was not used. Interestingly, use of topical treatment was not associated with disease progression (Table 5). Patch/plaque T-stage (T1 a/T2a vs T1 b/T2b) was the only independent clinical factor that was significantly associated with disease progression (Table 5). Therefore, we adjusted the PFS analysis by patch/plaque T- stage (T1 a/T2a vs T1 b/T2b) and found that the three-miRNA classifier remained a powerful and independent predictor of disease progression; this was the case both in the entire cohort, HR, 3.79; (95% CI, 2.17-6.65); P= 0.000005, the discovery cohort, HR, 4.35 (95% CI, 2.03-9.33), P= 0.000087, and in the independent validation cohort, HR, 3.47; (95% CI, 1 .30-9.24); P=0.02. In addition, stratification by clinical prognostic factors revealed that the three-miRNA classifier remained a significant prognostic marker of disease progression in patients with early-stage MF (Figure 4). Of notice, use of topical treatment and the year of diagnosis had no impact on the three-miRNA classifier. The prognostic accuracy was clearly higher of the three-miRNA classifier than of the existing clinical prognostic factors as well as the individual miRNAs (Figure 5).
Notably, assessing proportion of overall survival (OS) in the entire patient cohort showed that patients predicted to have a high risk of disease progression had a significantly decreased OS compared with the low risk group, HR 2.39 (95% CI 1 .46- 3.92) P= 0.00086, Figure 6. The 5- and 10-year OS for the high risk group was 73% (95% CI 60%-89%) and 51 % (95% CI 37%-71 %), respectively, and for the low risk group 84% (95% CI 77%-91 %) and 71 % (95% CI 62%-81 %), respectively. Thus, the identified three-miRNA classifier identified patients with high risk of disease
progression, which had a direct impact on the OS in patients diagnosed with early stage MF.
Table 1. Patient characteristics of the discovery cohort and the independent validation cohort Patient Discovery cohort Independent validation cohort characteristics
Number of Progressio Non- Number Progressi Non- patients n (%) n=31 progressio of on (%) progres (%) n=82 n (%) patients n=20 sion n=51 (%) n=72 (%) n=52
Sex
Male 54 (66) 19 (61) 35 (69) 38 (53) 10 (50) 28 (54)
Female 28 (34) 12 (39) 16 (31) 34 (47) 10 (50) 24 (46)
Age
<60 26 (32) 6 (19) 13 (25) 30 (42) 9 (45) 21 (40)
>60 56 (68) 25 (81) 38 (75) 42 (58) 11 (55) 31 (60)
Clinical stage
IA 29 (35) 11 (35) 18 (35) 42 (58) 4 (20) 38 (73)
IB 52 (63) 20 (65) 32 (63) 29 (40) 15 (75) 14 (27)
IIA 1 (2) 0 1 (2) 1 (1) 1 (5) 0
T-stage
Tl 29 (35) 11 (35) 18 (35) 42 (58) 4 (20) 38 (73)
Tla 5 0 5 15 0 15
Tib 24 11 13 27 4 23
T2 53 (65) 20 (65) 33 (65) 30 (42) 16 (80) 14 (27)
T2a 4 1 3 1 1 0
T2b 49 19 30 29 15 14
CLIPi*
1. Low risk 10 (12) 3 (10) 7 (14) 19 (26) 4 (20) 15 (29)
2. Intermediate 32 (39) 11 (35) 21 (41) 30 (42) 8 (40) 22 (42) risk
3. High risk 40 (49) 17 (55) 23 (45) 23 (32) 8 (40) 15 (29)
Treatment!
No treatment 57 (70) 22 (71) 35 (69) 59 (82) 14 (70) 41 (79)
Topical treatment 25 (30) 9 (29) 16 (31) 13 (18) 6 (30) 11 (21)
CLIPi, cutaneous lymphoma international prognostic index.
*CLIPi group 1 = low risk (0-1 risk factors), CLIPi group 2= intermediate risk (2 risk factors), CLIPi group 3= high risk (3-5 risk factors) (Ref: Benton EC et al Eur J Cancer.
2013;49(13):2859-2868.)
†Use of skin-directed therapies (topical corticosteroids, phototherapy or nitrogen mustard) upon diagnosis. No patients received systemic therapies. Table 2 Single miRNAs that can predict disease progression significantly after correction for multiple testing (Benjamini-Hocberg (BH) correction) in the entire patient cohort using a Cox proportional hazards regression.
miRNA id HR pr unit (95% CI) BH adjusted p-value hsa.miR.106b.5p 2,40 (1.72-3.33) 0.000001
hsa.miR.19a.3p 2,18 (1.62-2.94) 0.000001
hsa.miR.30e.5p 2,95 (1.96-4.43) 0.000001
hsa.miR.125a.5p 0,31 (0.18-0.54) 0,0012
hsa.miR.148a.3p 2,41 (1.57-3.71) 0,0020
hsa.miR.98.5p 1,58 (1.26-1.99) 0,0026
hsa.miR.101.3p 2,04 (1.42-2.94) 0,0026
hsa.miR.22.3p 2,47 (1.55-3.94) 0,0026
hsa.miR.660.5p 1,84 (1.35-2.52) 0,0026
hsa.miR.19b.3p 2.00 (1.37-2.92) 0,0049
hsa.let.7i.5p 2,23 (1.43-3.47) 0,0053
hsa.miR.21.5p 1,58 (1.23-2.08) 0,0053
hsa.miR.28.5p 2,05 (1.36-3.08) 0,0068
hsa.miR.424.5p 1,44 (1.17-1.78) 0,0081
hsa.miR.34a.5p 2,34 (1.42-3.85) 0,0083
hsa.let.7b.5p 0,39 (0.22-0.68) 0,0084
hsa.miR.1247.5p 0,69 (0.55-0.86) 0,0084
hsa.miR.211.5p 0,69 (0.55-0.86) 0,0084
hsa.miR.22.5p 1,58 (1.20-2.08) 0,0088
hsa.miR.454.3p 1,41 (1.14-1.73) 0,0093
hsa.miR.425.5p 1,84 (1.26-2.67) 0,011
hsa.miR.29c.3p 2,12 (1.33-3.39) 0,012
hsa.miR.92a.3p 0,40 (0.22-0.71) 0,012
hsa.miR.374a.5p 1,49 (1.16-1.92) 0,012
hsa.miR.15a.5p 1,82 (1.24-2.68) 0,013
hsa.miR.142.3p 1,43 (1.12-1.80) 0,015
hsa.miR.374b.5p 1,53 (1.16-2.03) 0,016
hsa.miR.142.5p 1,52 (1.15-2.00) 0,018
hsa.miR.205.5p 0,80 (0.69-0.94) 0,018
hsa.miR.338.3p 1,49 (1.14-1.94) 0,019
hsa.miR.185.5p 1,67 (1.17-2.38) 0,022
hsa.miR.29b.3p 1,71 (1.18-2.48) 0,022
hsa.miR.181b.5p 1,53 (1.14-2.07) 0,023
hsa.miR.376c.3p 1,43 (1.11-1.83) 0,023
hsa.miR.32.5p 1,37 (1.10-1.70) 0,023
hsa.miR.107 1,92 (1.21-2.05) 0,024 hsa.miR.193b.3p 0,52 (0.32-0.83) 0,026 hsa.miR.139.5p 0,72 (0.56-0.91) 0,029 hsa.miR.20a.5p 1,68 (1.15-2.47) 0,030 hsa.miR.130a.3p 1,65 (1.13-2.39) 0,032 hsa.miR.223.3p 1,38 (1.08-1.75) 0,032 hsa.miR.328.3p 0,72 (0.56-0.92) 0,032 hsa.miR.16.5p 1,72 (1.14-2.58) 0,034 hsa.miR.21.3p 1,38 (1.08-1.76) 0,034 hsa.miR.93.5p 1,80 (1.14-2.83) 0,038 hsa.miR.99b.5p 0,52 (0.31-086) 0,038 hsa.miR.140.5p 1,58 (1.11-2.25) 0,039 hsa.miR.128.3p 1,42 (1.08-1.86) 0,042 hsa.miR.18b.5p 1,34 (1.06-1.69) 0,043 hsa.miR.23b.3p 0,46 (0.25-0.85) 0,043 hsa.let.7g.5p 1,92 (1.13-3.26) 0,046 hsa.miR.148b.3p 1,50 (1.08-2.09) 0,046 hsa.miR.18a.5p 1,30 (1.05-1.56) 0,046 hsa.miR.532.5p 1,49 (1.08-2.05) 0,046 hsa.miR.192.5p 1,35 (1.06-1.72) 0,046
Table 3. Expression of the top 123 regulated miRNAs in the discovery cohort compared to healthy age- and sex-matched controls. The miRNA expression is presented as the mean of the normalized Cp values.
miRNA id MF HC mean Fold t-test BH
mean expression change corr. P
express value
ion
hsa-miR-155-5p -0.773 -4.819 16.52 < .0001
hsa-miR-142-5p -3.873 -7.603 13.27 < .0001
hsa-miR-21-3p -5.087 -8.778 12.91 < .0001
hsa-miR-142-3p 0.200 -2.453 6.29 < .0001
hsa-miR- 146a-5p -1.081 -3.524 5.44 < .0001
hsa-miR-150-5p 1.818 -0.597 5.33 < .0001
hsa-miR-21-5p 2.412 -0.003 5.33 < .0001
hsa-miR- 146b-5p -4.140 -6.187 4.13 < .0001
hsa-miR- 1248 -1.038 -3.020 3.95 < .0001
hsa-miR-361-3p -4.981 -6.769 3.45 < .0001 hsa-miR-766-3p -4.552 -6.239 3.22 < .0001 hsa-miR-223-3p 0.465 -1.196 3.16 < .0001 hsa-miR- 18b-5p -5.216 -6.778 2.95 < .0001 hsa-miR- 18a-5p -5.055 -6.567 2.85 < .0001 hsa-miR-32-5p -5.678 -7.169 2.81 < .0001 hsa-miR- 128-3p -4.802 -6.199 2.63 < .0001 hsa-miR- 15 a-5p -1.180 -2.527 2.54 < .0001 hsa-miR-484 -2.995 -4.339 2.54 < .0001 hsa-miR-345-5p -3.311 -4.654 2.54 < .0001 hsa-miR-29a-3p -0.491 -1.803 2.48 < .0001 hsa-miR-342-3p -0.087 -1.398 2.48 < .0001 hsa-miR-34a-5p -1.406 -2.699 2.45 < .0001 hsa-miR-425-5p -2.914 -4.206 2.45 < .0001 hsa-miR-29b-3p -2.463 -3.743 2.43 < .0001 hsa-miR-425-3p -5.824 -7.060 2.35 < .0001 hsa-miR-424-5p -5.590 -6.730 2.20 < .0001 hsa-miR- 185-5p -2.259 -3.387 2.19 < .0001 hsa-miR-362-5p -7.283 -8.374 2.13 < .0001 hsa-miR-454-3p -5.322 -6.403 2.12 < .0001 hsa-miR-423-5p -2.601 -3.662 2.09 < .0001 hsa-miR-22-3p -1.804 -2.848 2.06 < .0001 hsa-miR- 192-5p -5.424 -6.370 1.93 < .0001 hsa-miR-29c-3p -1.914 -2.858 1.92 < .0001 hsa-let-7i-5p -0.750 -1.678 1.90 < .0001 hsa-miR-93-5p -0.937 -1.845 1.88 < .0001 hsa-miR-660-5p -3.510 -4.394 1.85 < .0001 hsa-miR-652-3p -2.916 -3.790 1.83 < .0001 hsa-miR- 106a-5p -0.800 -1.673 1.83 < .0001 hsa-miR- 106b-5p -3.426 -4.262 1.78 < .0001 hsa-miR- 103 a-3p 1.076 0.261 1.76 < .0001 hsa-miR- 16-5p 2.633 1.851 1.72 < .0001 hsa-miR-181a-5p -0.071 -0.853 1.72 < .0001 hsa-miR- 193a-3p -5.909 -6.679 1.71 < .0001 hsa-miR-132-3p -3.362 -4.121 1.69 < .0001 hsa-miR- 107 -1.009 -1.764 1.69 < .0001 hsa-miR-25-3p -1.449 -2.161 1.64 < .0001 hsa-miR-98-5p -5.319 -6.012 1.62 < .0001 hsa-miR- 18 lb-5p -3.336 -3.994 1.58 < .0001 hsa-miR-191-5p -1.175 -1.813 1.56 < .0001 hsa-miR-532-5p -4.0322 -4.663 1.55 < .0001 hsa-miR-224-5p -6.064 -6.671 1.52 < .0001 hsa-miR-324-3p -2.937 -3.542 1.52 < .0001 hsa-miR-93-3p -5.201 -5.781 1.49 .0003 hsa-miR-20a-5p -0.641 -1.193 1.47 < .0001 hsa-miR-339-5p -2.549 -3.029 1.39 < .0001 hsa-miR- 15b-5p -3.588 -4.060 1.39 .0037 hsa-miR-28-5p -3.103 -3.565 1.38 < .0001 hsa-miR-92b-3p -6.500 -6.956 1.37 .0082 hsa-miR-331-3p -2.450 -2.886 1.35 < .0001 hsa-let-7g-5p 0.705 0.285 1.34 < .0001 hsa-miR-455-5p -5.736 -6.150 1.33 .020 hsa-miR-324-5p -3.503 -3.907 1.32 .0025 hsa-miR-409-3p -4.459 -4.855 1.32 .013 hsa-miR- 140-3p -1.749 -2.142 1.31 .0002 hsa-miR-708-5p -4.079 -4.467 1.31 .028 hsa-miR-423-3p -0.907 -1.272 1.29 < .0001 hsa-miR-505-3p -5.791 -6.138 1.27 .011 hsa-miR- 148b-3p -4.191 -4.532 1.27 .002 hsa-miR- 130a-3p -4.243 -4.574 1.26 .0017 hsa-miR- 199a-5p -0.418 -0.714 1.23 .049 hsa-miR- 127-3p -3.069 -3.301 1.17 .036 hsa-let-7d-5p -1.589 -1.782 1.14 .019 hsa-miR-23a-3p 2.868 3.093 -1.17 .0007 hsa-miR-30b-5p -0.392 -0.160 -1.17 .012 hsa-miR-30c-5p -0.139 0.100 -1.18 .0002 hsa-miR- 199a-3p -0.349 -0.050 -1.23 .017 hsa-miR-26b-5p -3.232 -2.917 -1.24 .0075 hsa-miR-30d-5p -1.241 -0.917 -1.25 < .0001 hsa-miR-99b-5p -2.000 -1.656 -1.27 .0008 hsa-miR-27b-3p 0.417 0.763 -1.27 .0040 hsa-miR-151a-5p -1.834 -1.487 -1.27 < .0001 hsa-miR-210-3p -2.616 -2.236 -1.30 .0013 hsa-miR- 14 l-3p -2.382 -1.990 -1.31 .045 hsa-miR-99a-3p -5.356 -4.951 -1.32 .0001 hsa-miR- 152-3p -2.448 -2.018 -1.35 < .0001 hsa-let-7e-5p -1.679 -1.247 -1.35 < .0001 hsa-miR- 182-5p -5.701 -5.266 -1.35 .022 hsa-let-7a-5p 3.077 3.518 -1.36 < .0001 hsa-miR-328-3p -3.533 -3.075 -1.37 .0022 hsa-miR-23b-3p 1.738 2.201 -1.38 < .0001 hsa-miR- 1247-5p -4.609 -4.141 -1.38 .0077 hsa-miR- 126-3p 0.457 0.951 -1.41 < .0001 hsa-let-7b-5p 1.915 2.466 -1.46 < .0001 hsa-miR-101-3p -3.243 -2.677 -1.48 .0004 hsa-miR-26a-5p -0.017 0.550 -1.48 < .0001 hsa-miR-200c-3p 0.753 1.344 -1.51 < .0001 hsa-miR-151a-3p -4.948 -4.341 -1.52 < .0001 hsa-miR- 126-5p -5.270 -4.651 -1.54 < .0001 hsa-miR-205-5p 3.869 4.504 -1.55 .0002 hsa-miR- 199b-5p -1.594 -0.954 -1.56 < .0001 hsa-miR- 196b-5p -4.522 -3.844 -1.60 < .0001 hsa-miR- 195 -5p -1.844 -1.145 -1.62 < .0001 hsa-miR-203a 1.601 2.303 -1.63 .0001 hsa-miR-148a-3p -3.074 -2.363 -1.64 < .0001
hsa-miR-200a-3p -4.179 -3.466 -1.64 < .0001
hsa-miR-30e-3p -4.559 -3.844 -1.64 < .0001
hsa-miR-214-3p -2.134 -1.384 -1.68 < .0001
hsa-miR-125a-5p 0.600 1.358 -1.69 < .0001
hsa-miR-574-3p -2.126 -1.362 -1.70 < .0001
hsa-miR- 193a-5p -5.396 -4.600 -1.74 < .0001
hsa-let-7c-5p -0.190 0.622 -1.76 < .0001
hsa-miR- 139-5p -3.862 -2.981 -1.84 < .0001
hsa-miR-30a-5p -4.966 -3.993 -1.96 < .0001
hsa-miR-200b-3p -2.054 -1.075 -1.97 < .0001
hsa-miR- 100-5p -0.878 0.171 -2.07 < .0001
hsa-miR- 145 -5p 2.411 3.463 -2.07 < .0001
hsa-miR-30a-3p -5.441 -4.317 -2.18 < .0001
hsa-miR- 196a-5p -4.385 -3.220 -2.24 < .0001
hsa-miR- 149-5p -3.066 -1.900 -2.24 < .0001
hsa-miR- 10b-5p -2.138 -0.900 -2.36 < .0001
hsa-miR- 125b-5p 2.420 3.668 -2.38 < .0001
hsa-miR-99a-5p 0.320 1.677 -2.56 < .0001
hsa-miR-338-3p -5.597 -4.203 -2.63 < .0001
MF, mycosis fungoides; HC, lealthy control; 3H corr, Benjamini-Hoc
Expression of the top 123 regulated miRNAs in the discovery cohort compared with healthy age- and sex-matched controls as described in materials and methods. The miRNA expression is presented as the mean of the normalized Cp values. The normalization was performed using the global mean approach, as described in the materials and methods section.
Table 4 Univariate association of the 123 miRNAs with progression free survival in the discovery cohort, validation cohort and the entire cohort
Discovery cohort Independent validation Entire cohort
cohort
miRNA HR per unit p- HR (per unit p- HR per unit p- id (95% CI) valu 95% CI) value (95% CI) value
Figure imgf000051_0001
Figure imgf000052_0001
Figure imgf000053_0001
Figure imgf000054_0001
Figure imgf000055_0001
Table 5 Univariate association of clinical characteristics, clinical prognostic factors, single miRNAs and the three-miRNA classifier with progression-free survival
Figure imgf000056_0001
HR, hazard ratio; CI, confidence interval; CLIPi, cutaneous lymphoma international prognostic index.
*Use of skin-directed therapies (topical corticosteroids, phototherapy or nitrogen mustard) upon diagnosis. No patients received systemic therapies.
†CLIPi group 1 = low risk (0-1 risk factors), CLIPi group 2= intermediate risk (2 risk factors), CLIPi group 3= high risk (3-5 risk factors) (Benton EC et al Eur J Cancer. 2013;49(13):2859-2868).

Claims

Claims
A method of prognosing cutaneous T-cell lymphoma in an individual, said method comprising:
i. providing a test sample from said individual;
ii. determining the expression level of at least one miRNA in said test sample, wherein the at least one miRNA is selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
The method according to claim 1 , wherein said test sample comprises tissue cells.
The method according to anyone of the preceding claims, comprising determining the expression levels of at least two miRNA's.
The method according to anyone of the preceding claims comprising determining the expression levels of at least three miRNA's.
The method according to anyone of the preceding claims comprising determining the expression levels of at least 4, such as at least 5, at least 6, at least 7, at least 8, at least 9 or such as at least 10 miRNA's.
6. The method according to anyone of the preceding claims comprising
determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p.
7. The method according to anyone of the preceding claims comprising
determining the expression level of at least one miRNA selected from the group consisting of miR-106b-5p and miR-148a-3p.
8. The method according to anyone of the preceding claims comprising
determining the expression level of at least two miRNA's selected from the group consisting of miR-106b-5p, miR-148a-3p and miR-338-3p.
9. The method according to anyone of the preceding claims comprising
determining the expression level of miR-106b-5p and miR-148a-3p.
10. The method according to anyone of the preceding claims comprising
determining the expression level of miR-106b-5p, miR-148a-3p and miR- 3p.
1 1 . The method according to anyone of the preceding claims, wherein said
individual has Mycosis fungoides at an early stage.
12. The method according to claim 1 1 , wherein said early stage is stage IA-IIA.
13. The method according to anyone of the preceding claims, wherein said
prognosing includes determining the risk of disease progression.
14. The method according to claim 13, wherein the risk of disease progression. in said individual is determined by calculating a risk score R.
15. The method according to claim 14 wherein the risk score R is a linear
combination of one or more normalised Cp levels of one or more miRNAs.
16. The method according to anyone of claims 14 and 15, wherein R is calculated using the formula:
R= βι * Cpi + β2 * Cp2 + ....+ βη-1 * Cpn-1 + βη * Cpn.
wherein Cpi ...Cpn refers to the normalized crossing point value for a given miRNA, wherein β-ι,.. βη are coefficients calculated by linear regression and wherein n is an integer and refers to the number of miRNA tested.
17. The method according to any of claims 13-16, wherein said disease
progression means that the stage of Mycosis fungoides progresses to stage IIB- IVB.
18. The method according to any of claims 13-17, wherein an individual having high or an increased risk of disease progression is subjected to systemic treatment.
19. The method according to claim 18, wherein said systemic treatment is selected from the group consisting of interferon alpha, bexarotene, methotrexate, corticosteroids, pegylated liposomal doxorubicin, histone deacetylase inhibitors (HDACi) such as eg. vorinostat or romidepsin, alemtuzumab and psoralen plus ultraviolet A light.
20. The method according to anyone of the preceding claims wherein said
individual is a human being.
21 . The method according to anyone of the preceding claims, said wherein said level(s) of miRNA is/are determined by amplifying a portion of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21.5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
22. The method according to claim 21 , wherein said level(s) of miRNA is/are determined using an oligonucleotide probe capable of binding to the amplified portion of said at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101 .3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1.5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
23. A method of determining a treatment regime of an individual having cutaneous T-cell lymphoma said method comprising the steps of
i. determining the risk of disease progression in an individual by the method as defined in anyone of the preceding claims
ii. selecting individuals having a high risk of disease progression
iii. subjecting said individual to systemic treatment.
24. The method according to claim 23, wherein said individual having a high risk of disease progression has Mycosis fungoides at stage IIB-IVB.
25. The method according to anyone of claims 23-24, wherein said systemic
treatment is selected from the group consisting of interferon alpha, bexarotene, methotrexate, corticosteroids, pegylated liposomal doxorubicin, histone deacetylase inhibitors (HDACi) such as eg. vorinostat or romidepsin, alemtuzumab and psoralen plus ultraviolet A light.
26. The method according to anyone of claims 23-25, wherein said individual is a human being.
27. A kit for determining the risk of disease progression in an individual having cutaneous T-cell lymphoma, said kit comprising at least one probe or at least one pair of probe that specifically bind to a region of at least one miRNA selected from the group consisting of miR.106b.5p, miR.19a.3p, miR.30e.5p, miR.125a.5p, miR.148a.3p, miR.98.5p, miR.101.3p, miR.22.3p, miR.660.5p, miR.19b.3p, let.7i.5p, miR.21 .5p, miR.28.5p, miR.424.5p, miR.34a.5p, let.7b.5p, miR.1247.5p, miR.21 1 .5p, miR.22.5p, miR.454.3p, miR.425.5p, miR.29c.3p, miR.92a.3p, miR.374a.5p, miR.15a.5p, miR.142.3p, miR.374b.5p, miR.142.5p, miR.205.5p, miR.338.3p, miR.185.5p, miR.29b.3p, miR.181 b.5p, miR.376c.3p, miR.32.5p, miR.107, miR.193b.3p, miR.139.5p, miR.20a.5p, miR.130a.3p, miR.223.3p, miR.328.3p, miR.16.5p, miR.21 .3p, miR.93.5p, miR.99b.5p, miR.140.5p, miR.128.3p, miR.18b.5p, miR.23b.3p, let.7g.5p, miR.148b.3p, miR.18a.5p, miR.532.5p and miR.192.5p.
28. The kit according to claim 27, wherein said at least one probe or at least one pair of probe specifically bind to a region of said at least one miRNA under amplification conditions.
29. The kit according to anyone of claims 27-28, further comprising a microarray chip, wherein said probe(s) is/are located on said microarray chip.
30. The kit according to anyone of claims 27-28, further comprising a QPCR
Microfluidic Card.
31 . The kit according to anyone of claims 27-30 further comprising at least one additional component.
32. The kit according to anyone of claims 27-31 , wherein said additional component comprises means for extracting RNA, such as miRNA, from a sample.
33. The kit according to claims 27-29 and 31 -32, wherein said additional
component comprises reagents for performing microarray analysis.
34. The kit according to claims 27-28 and 30-32, wherein said additional
component comprises reagents for performing QPCR analysis.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012115885A1 (en) * 2011-02-22 2012-08-30 Caris Life Sciences Luxembourg Holdings, S.A.R.L. Circulating biomarkers
WO2013107459A2 (en) * 2012-01-16 2013-07-25 Herlev Hospital Microrna for diagnosis of pancreatic cancer and/or prognosis of patients with pancreatic cancer by blood samples
WO2014111561A1 (en) * 2013-01-21 2014-07-24 Deutsches Krebsforschungszentrum Serum mirna-142-3p as prognostic cancer marker

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012115885A1 (en) * 2011-02-22 2012-08-30 Caris Life Sciences Luxembourg Holdings, S.A.R.L. Circulating biomarkers
WO2013107459A2 (en) * 2012-01-16 2013-07-25 Herlev Hospital Microrna for diagnosis of pancreatic cancer and/or prognosis of patients with pancreatic cancer by blood samples
WO2014111561A1 (en) * 2013-01-21 2014-07-24 Deutsches Krebsforschungszentrum Serum mirna-142-3p as prognostic cancer marker

Non-Patent Citations (18)

* Cited by examiner, † Cited by third party
Title
AGAR NS ET AL., JOURNAL OF CLINICAL ONCOLOGY: OFFICIAL JOURNAL OF THE AMERICAN SOCIETY OF CLINICAL ONCOLOGY, vol. 28, no. 31, 2010, pages 4730 - 4739
BENTON EC ET AL., EUROPEAN JOURNAL OF CANCER, vol. 49, no. 13, 2013, pages 2859 - 2868
COX DR: "Regression models and life tables (with discussion", J R STATIST SOC B., vol. 34, 1972, pages 187 - 220
DÓRA MAROSVÁRI ET AL: "Altered MicroRNA Expression in Folliculotropic and Transformed Mycosis Fungoides", PATHOLOGY ONCOLOGY RESEARCH, vol. 21, no. 3, 20 February 2015 (2015-02-20), HU, pages 821 - 825, XP055442593, ISSN: 1219-4956, DOI: 10.1007/s12253-015-9897-8 *
FUMITO ABE ET AL: "Histone deacetylase inhibitors inhibit metastasis by restoring a tumor suppressive microRNA-150 in advanced cutaneous T-cell lymphoma", ONCOTARGET, vol. 8, no. 5, 7 December 2016 (2016-12-07), pages 7572 - 7585, XP055442585, DOI: 10.18632/oncotarget.13810 *
GIRARDI M ET AL., THE NEW ENGLAND JOURNAL OF MEDICINE, vol. 350, no. 19, 2004, pages 1978 - 1988
GRIFFITHS-JONES ET AL.: "miRBase: tools for microRNA genomics", NUCLEIC ACIDS RESEARCH, vol. 36, 2008, pages D154 - D158
JUAN SANDOVAL ET AL: "MicroRNA Expression Profiling and DNA Methylation Signature for Deregulated MicroRNA in Cutaneous T-Cell Lymphoma", THE JOURNAL OF INVESTIGATIVE DERMATOLOGY : OFFICIAL JOURNAL OF THE SOCIETY FOR INVESTIGATIVE DERMATOLOGY AND THE EUROPEAN SOCIETY FOR DERMATOLOGICAL RESEARCH, vol. 135, no. 4, 1 April 2015 (2015-04-01), US, pages 1128 - 1137, XP055442592, ISSN: 0022-202X, DOI: 10.1038/jid.2014.487 *
LINDAHL LM ET AL., JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY, vol. 71, no. 3, September 2014 (2014-09-01), pages 529 - 535
LISE M. LINDAHL ET AL: "Prognostic miRNA classifier in early-stage mycosis fungoides: development and validation in a Danish nationwide study", BLOOD, 5 December 2017 (2017-12-05), US, XP055442587, ISSN: 0006-4971, DOI: 10.1182/blood-2017-06-788950 *
M G NARDUCCI ET AL: "MicroRNA profiling reveals that miR-21, miR486 and miR-214 are upregulated and involved in cell survival in Sézary syndrome", CELL DEATH AND DISEASE, vol. 2, no. 4, 1 April 2011 (2011-04-01), pages e151, XP055043454, DOI: 10.1038/cddis.2011.32 *
OLSEN E ET AL., BLOOD, vol. 110, no. 6, 2007, pages 1713 - 1722
TIBSHIRANI R., STATISTICS IN MEDICINE, vol. 16, no. 4, 1997, pages 385 - 395
TIBSHIRANI R: "The lasso method for variable selection", THE COX MODEL. STAT MED., vol. 16, no. 4, 28 February 1997 (1997-02-28), pages 385 - 395, XP009128750, DOI: doi:10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3
TRAUTINGER F ET AL., EUROPEAN JOURNAL OF CANCER, vol. 42, no. 8, 2006, pages 1014 - 1030
TROYANSKAYA O ET AL., BIOINFORMATICS, vol. 17, no. 6, 2001, pages 520 - 525
ULRIK RALFKIAER ET AL: "MicroRNA expression in early mycosis fungoides is distinctly different from atopic dermatitis and advanced cutaneous T-cell lymphoma", ANTICANCER RESEARCH, 1 December 2014 (2014-12-01), Greece, pages 7207, XP055442600, Retrieved from the Internet <URL:http://ar.iiarjournals.org/content/34/12/7207.full.pdf> *
ZHANG JX ET AL., THE LANCET ONCOLOGY, vol. 14, no. 13, 2013, pages 1295 - 1306

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