Genetic Construct

Abstract

The invention relates to genetic constructs comprising at least one microRNA target site, and vectors comprising such constructs. The genetic constructs and vectors can be used in diagnosis and therapy of a range of disorders, including cancers, for example T-cell acute lymphoblastic leukaemia (T-ALL).

Claims

1. A genetic construct comprising: (i) a first promoter operably linked to a first nucleic acid sequence encoding a therapeutically active molecule or a reporter molecule, wherein the first nucleic acid sequence comprises at least one microRNA (miRNA) target site; and (ii) a second promoter operably linked to a second nucleic acid sequence encoding an inhibitor of the first promoter and/or the therapeutically active molecule or reporter molecule, and wherein the second nucleic acid sequence comprises at least one miRNA target site, wherein the at least one miRNA target site of the first and second nucleic acid sequences are different.

2. The genetic construct according to claim 1, wherein the at least one miRNA target site of the second nucleic acid sequence is a target site of an miRNA that is different to an miRNA capable of targeting the at least one miRNA target site of the first nucleic acid sequence.

3. The genetic construct according to either claim 1 or claim 2, wherein the first nucleic acid sequence comprises at least one miRNA target site or species of miRNA target site, at least two miRNA target sites or species of miRNA target site, at least three miRNA target sites or species of miRNA target site, at least four miRNA target sites or species of miRNA target site, or at least five miRNA target sites or species of miRNA target site, optionally wherein there is at least one copy of each miRNA target site, at least two copies of each miRNA target site, at least three copies of each miRNA target site, at least four copies of each miRNA target site, or at least five copies of each miRNA target site, or species of miRNA target site.

4. The genetic construct according to any preceding claim, wherein the at least one miRNA target site present in the first nucleic acid sequence is a target site for a miRNA that is not expressed in a diseased cell.

5. The genetic construct according to claim 4, wherein the diseased cell is a cancer cell, optionally wherein the diseased cell is a T-cell acute lymphoblastic leukaemia (T-ALL) cell.

6. The genetic construct according to any preceding claim, wherein the second nucleic acid sequence comprises at least one miRNA target site or species of miRNA target site, at least two miRNA target sites or species of miRNA target site, at least three miRNA target sites or species of miRNA target site, at least four miRNA target sites or species of miRNA target site, or at least five miRNA target sites or species of miRNA target site, optionally wherein there is at least one copy of each miRNA target site, at least two copies of each miRNA target site, at least three copies of each miRNA target site, at least four copies of each miRNA target site, or at least five copies of each miRNA target site, or species of miRNA target site.

7. The genetic construct according to any preceding claim, wherein the at least one miRNA target site present in the second nucleic acid sequence is a target site for a miRNA that is expressed in a diseased cell.

8. The genetic construct according to any preceding claim, wherein the reporter molecule is an optical reporter, a nuclear medicine reporter or an MRI reporter.

9. The genetic construct according to any preceding claim, wherein the therapeutically active molecule is a therapeutic protein and/or nucleic acid.

10. The genetic construct according to claim 9, wherein the nucleic acid is DNA, RNA or a chimeric DNA/RNA molecule.

11. The genetic construct according to any one of claims 1 to 9, wherein the therapeutic protein is selected from the group consisting of: an endonuclease, a chimeric antigen receptor, a viral protein and an apoptosis driver protein.

12. The genetic construct according to claim 11, wherein the therapeutic protein is an apoptosis driver protein selected from the group consisting of: Bax, Apoptin, E4orf4 and Bim.

13. The genetic construct according to claim 12, wherein the therapeutic protein is Bax, which comprises or consists of an amino acid sequence as substantially set out in SEQ ID No: 16, or a biologically active variant or fragment thereof.

14. The genetic construct according to claim 12, wherein the therapeutic protein is Apoptin, which comprises or consists of an amino acid sequence as substantially set out in SEQ ID No: 18, or a biologically active variant or fragment thereof.

15. The genetic construct according to claim 12, wherein the therapeutic protein is E4orf4, which comprises or consists of a sequence as substantially set out in SEQ ID No: 20, or a biologically active variant or fragment thereof.

16. The genetic construct according to claim 12, wherein the therapeutic protein is Bim, which comprises or consists of a sequence as substantially set out in SEQ ID No: 25, or a biologically active variant or fragment thereof.

17. The genetic construct according to any preceding claim, wherein the second promoter is arranged in an opposite orientation in the construct to the first promoter.

18. The genetic construct according to any preceding claim, wherein the inhibitor encoded by the second nucleic acid sequence is an inhibitor of the first promoter and wherein the inhibitor of the first promoter is a Lac operon, wherein the second nucleic acid sequence comprises a Lac repressor and the first promoter comprises a Lac operator regulator site.

19. The genetic construct according to any preceding claim, wherein the genetic construct comprises a nucleic acid sequence substantially as set out in any one of SEQ ID Nos: 5, 22 to 24, 27, or 78 to 82, or a fragment or variant thereof.

20. A recombinant vector comprising the genetic construct according to any preceding claim.

21. The genetic construct according to any one of claims 1 to 19, or the vector according to claim 20, for use in therapy.

22. The genetic construct according to any one of claims 1 to 19, or the vector according to claim 20, for use in treating, preventing or ameliorating cancer.

23. A pharmaceutical composition comprising the genetic construct according to any one of claims 1 to 19, or the vector according to claim 20, and optionally a pharmaceutically acceptable vehicle.

24. The genetic construct according to any one of claims 1 to 19, or the vector according to claim 20, for use in diagnosis.

25. The genetic construct according to any one of claims 1 to 19, or the vector according to claim 20, for use in diagnosing cancer.

26. A method of diagnosis or prognosis, the method comprising detecting the reporter molecule of the genetic construct according to any one of claims 1 to 19, or the vector according to claim 20, in a sample obtained from a subject.

27. A method of diagnosing or prognosing cancer in a subject, the method comprising detecting the reporter molecule of the genetic construct according to any one of claims 1 to 19, or the vector according to claim 20, in a sample obtained from a subject.

Description

[0280] For a better understanding of the invention, and to show how embodiments of the same may be carried into effect, reference will now be made, by way of example, to the accompanying Figures, in which:-

[0281] FIG. 1 shows a schematic representation of miRNA-mediated silencing of a target mRNA. Both mRNAs and miRNAs are transcribed from their gene precursors. The miRNAs then bind to complementary regions of their target mRNAs leading to their degradation.

[0282] FIG. 2 shows a schematic representation of one embodiment of the microRNA-detector system and associated genetic construct of the invention for therapeutic gene delivery in T-ALL cells.

[0283] FIG. 3 shows microRNA relative expression in T-ALL and non-T-ALL cells determined by RT-qPCR and calculated using the 2.sup.-ΔΔCt method. * p<0.05; *** p<0.0001.

[0284] FIG. 4 shows a schematic representation of one embodiment of a pCDH-EF1-MCS-T2A-GFP (PGK-Puro) expression vector from SBI.

[0285] FIG. 5 shows a schematic representation of a bidirectional lentiviral expression vector (“bdLV”) modified to express the Lac operon depicting a 2-step approach.

[0286] FIG. 6 shows the results from cloning of Lac operator sequences (LacO) downstream of the EF1 promoter. A) shows GFP expression of 293T cells transfected with bdLV vector or bdLV_LacO vector. B.i) shows GFP expression of 293T cells transfected with bdLV_LacO vector or BdLV_LacO and LacI vectors. B.ii) shows GFP expression of 293T cells co-transfected with bdLV_LacO and LacI vectors and treated or not with IPTG (Isopropyl β-D-1-thiogalactopyranoside) for 24 and 48h. Unt.-untransfected.

[0287] FIG. 7 shows the results from cloning of the Lac repressor (LacI) downstream of PGK promoter. GFP expression of 293T cells transfected with bdLV_LacO vector or bdLV_LacI_LacO vector and treated with IPTG (Intensity and GeoMean). Unt.-untransfected.

[0288] FIG. 8 shows schematic representations of two embodiments of the microRNA detector system (A and B) and associated genetic constructs with the possible combinations of microRNA target sites C, D, E, F G, H, I, J, K and L).

[0289] FIGS. 9A-9B show the in vitro validation of the efficiency and specificity of the microRNA-detectors with target sequences for miR-29a and miR-149. T-ALL (A) and non-T-ALL (B) cells were transduced with the microRNA-detectors BdLV_miR29a_4xT, BdLV_miR149_4xT, and BdLV_miR29a_4xT_miR149_4xT. GFP expression was analysed by flow cytometry and used as readout to determine the efficiency of the detectors to repress the reporter gene expression.

[0290] FIGS. 10A-10B show the in vitro validation of the efficiency and specificity of the microRNA-detectors with target sequences for miR-128a and miR-153. T-ALL cells were transduced with the microRNA-detectors BdLV_miR128a_4xT, BdLV_miR153_4xT and BdLV_miR128a_4xT_miR153_4xT. GFP expression was analyzed by flow cytometry and used as readout to determine the efficiency of the microRNA-detectors to de-repress the reporter gene promoter through LacI.

[0291] FIG. 11 shows in vitro validation of a construct comprising dual miRNA target sites.

[0292] FIG. 12 shows the in vitro validation of the efficiency and specificity of the micro-RNA detectors comprising two, three or four miRNA target sites.

[0293] FIG. 13 shows the in vitro validation of the efficiency and specificity of the micro-RNA detectors in cultures of T-ALL and non-T-ALL cells transduced with non-integrative lentiviral vectors.

EXAMPLES

Example 1 - Overview of a Novel MicroRNA-Detector Which Enables T-ALL Identification and Selective Inhibition

[0294] In cancer, microRNA expression profiles have been shown to distinguish tumour cells from normal cells, and to discriminate tumours of different developmental origin and their differentiation state (8, 9, 14, 15). Therefore, the inventors took advantage of T-ALL-specific microRNA expression profiles to develop a microRNA-detector system (i.e. the recombinant genetic construct of the invention) that uses microRNAs to: (1) identify T-ALL cells, and then (2) regulate the expression of a therapeutic gene (an apoptosis-inducing gene) into leukaemia cells. Based on a pre-determined microRNA profile that is specific to T-ALL cells only, when expressed inside a host cell, the construct first determines whether the host cells are leukaemia cells and, if so, the construct then induces cell death. Thus, a positive match between the expression of specific microRNAs inside a T-ALL cell and the construct results in the delivery of a therapeutic gene to those T-ALL cells, inducing their death but not of the normal healthy cells (see FIG. 2A). The intrinsic ability of this system to distinguish between a T-ALL cell and a non-T-ALL cell within the body of the patient is, hence, a unique aspect of the invention. This therefore provides the significant advantage over other gene therapy technologies applied to precision oncology, and it has been deliberately designed to provide the best possible efficacy and safety outcomes for patients.

[0295] The delivery of the therapeutic gene is regulated both by microRNAs which are present only (or highly expressed) in T-ALL cells as well as microRNAs which are specifically absent (or significantly less expressed) in those cells. For example, referring to FIG. 2B, assuming that a leukaemia cell can be discriminated from normal cells by the absence of the microRNAs A and B, and by the presence of the microRNAs C and D, then, the therapeutic gene will only be delivered if: (1) microRNAs A and B are absent; and (2) microRNAs C and D are expressed in the same cell (see FIG. 2B).

[0296] MicroRNAs have been previously explored to negatively regulate gene expression. However, the present invention uses the concomitant presence and absence of specific microRNAs to positively regulate the expression of the therapeutic gene. This dual layer of regulation is achieved by the use of a bidirectional expression vector and a negative feedback loop. Such a system has not been applied before and increases the specificity of the technology to deliver the therapeutic gene only to the target cells, maximizing drug efficacy and safety, and patients’ therapeutic outcome (see FIG. 2C).

[0297] This innovative technology has the potential to effectively circumvent the lack of specificity in T-ALL therapy. Importantly, it will serve as proof-of-concept that this strategy can be applied to the development of similar personalized therapies in other cancer types in which there are variances in microRNA expression profiles.

Materials and Methods

Bioinformatics Analysis

[0298] To define a microRNA expression profile that is specific of T-ALL cells, the inventors collected microRNA expression data from publicly available human datasets. The inventors initially identified 10 human datasets that include T-ALL samples (1-10). Of these, four were excluded for lacking non-tumor samples (1-4) and two others for the impossibility to access the raw data (5, 6). For each one of the datasets analyzed (7-10), the inventors compared the non-T-ALL samples (control group) with the T-ALL samples (T-ALL group). The samples analyzed in the control groups varied between studies and included healthy tissue of lung, colon, bladder, brain, kidney, breast, total bone marrow (BM) cells, total thymocytes, hematopoietic CD34+ BM cells, CD4+ T cells, CD8+ T cells and CD4+CD8+CD3+ T-cells. The T-ALL groups included T-ALL primary cells and cell lines.

[0299] To be considered up-regulated in the T-ALL samples, the minimum expression value of a certain miRNA in that group had to be higher than the maximum expression value of that microRNA in the control group. In the same way, when the minimum expression value of a microRNA in the control group was higher than the maximum expression value in the T-ALL group, that miRNA was considered down-regulated in the T-ALL samples. Using this classification system, the inventors were able to identify 12 miRNAs which were down-regulated and up-regulated in the different datasets.

[0300] Subsequently, the inventors established a further T-ALL-specific microRNA expression profile by bioinformatics analyses of publicly available microRNA data obtained from human T-ALL cells and normal cells and tissues. These datasets encompassed approximately 140 T-ALL cell lines and patient cells and approximately 480 normal tissue samples including brain, liver, kidney, lung, heart, breast, bladder, colon, uterus, skin, ovary, pancreas, prostate, stomach, testis, meninges, thyroid, thymus, bone marrow, spleen, lymph nodes and peripheral blood. The hematopoietic and lymphoid organs covered different lineages and different differentiation stages, including hematopoietic stem and precursor cells.

[0301] This analysis identified 25 microRNAs, as shown in Table 1 below.

TABLE-US-00077 Expression in T-ALL microR NA ID Accession Number Sequence Target sequence up-regulated hsa-miR-3687 MIMAT001 8115 CCCGGACAGGCGUUCGU GCGACGU (SEQ ID No: 67) ACGTCGCACGAACGCCT GTCCGGG (SEQ ID No: 56) up-regulated hsa-miR-92a-2-5p MIMAT 0004508 GGGUGGGGAUUUGUUG CAUUAC (SEQ ID No: 68) GTAATGCAACAAATCCC CACCC (SEQ ID No: 57) up-regulated hsa-miR-20b-3P MIMAT 0004752 ACUGUAGUAUGGGCACU UCCAG (SEQ ID No: 69) CTGGAAGTGCCCATACT ACAGT (SEQ ID No: 58) up-regulated hsa-miR-6087 MIMAT002 UGAGGCGGGGGGGCGAG C (SEQ ID No: 70) GCTCGCCCCCCCGCCTC A (SEQ ID No: 59) up-regulated hsa-miR-106a-3p MIMAT000 4517 CUGCAAUGUAAGCACUU CUUAC (SEQ ID No: 71) GTAAGAAGTGCTTACAT TGCAG (SEQ ID No: 60) up-regulated hsa-miR-7704 MIMAT003 oo19 CGGGGUCGGCGGCGACG UG (SEQ ID No: 72) CACGTCGCCGCCGACCC CG (SEQ ID No: 61) up-regulated hsa-miR-5701 MIMAT002 2494 UUAUUGUCACGUUCUGA UU (SEQ ID No: 73) AATCAGAACGTGACAAT AA (SEQ ID No: 62) up-regulated hsa-miR-766-5p MIMAT002 2714 AGGAGGAAUUGGUGCUG GUCUU (SEQ ID No: 74) AAGACCAGCACCAATTC CTCCT (SEQ ID No: 63) up-regulated hsa-miR-3609 MIMAT001 7986 CAAAGUGAUGAGUAAUA CUGGCUG (SEQ ID No: 75) CAGCCAGTATTACTCAT CACTTTG (SEQ ID No: 64) up-regulated hsa-miR-3615 MIMAT001 7994 UCUCUCGGCUCCUCGCG GCUC (SEQ ID No: 76) GAGCCGCGAGGAGCCG AGAGA (SEQ ID No: 65) up-regulated hsa-miR-4746-5p MIMAT001 9880 CCGGUCCCAGGAGAACC UGCAGA (SEQ ID No: 77) TCTGCAGGTTCTCCTGG GACCGG (SEQ ID No: 66) down-regulated hsa-miR-539-5p MIMAT0 003163 GGAGAAAUUAUCCUUGG UGUGU (SEQ ID No: 42) ACACACCAAGGATAATT TCTCC (SEQ ID No: 28) down-regulated hsa-miR-487a-3p MIMAT000 2178 AAUCAUACAGGGACAUC CAGUU (SEQ ID No: 43) AACTGGATGTCCCTGTA TGATT (SEQ ID No: 29) down-regulated hsa-miR-655-3p MIMAT000 3331 AUAAUACAUGGUUAACC UCUUU (SEQ ID No: 44) AAAGAGGTTAACCATGT ATTAT (SEQ ID No: 30) down-regulated hsa-miR-411-3p MIMAT0 004813 UAUGUAACACGGUCCAC UAACC (SEQ ID No: 45) GGTTAGTGGACCGTGTT ACATA (SEQ ID No: 31) down-regulated hsa-miR-377-5P MIMAT000 4689 AGAGGUUGCCCUUGGUG AAUUC (SEQ ID No: 46) GAATTCACCAAGGGCAA CCTCT (SEQ ID No: 32) down-regulated hsa-miR-337-5P MIMAT000 4695 GAACGGCUUCAUACAGG AGUU (SEQ ID No: 47) AACTCCTGTATGAAGCC GTTC (SEQ ID No: 33) down-regulated hsa-miR-31-3p MIMAT000 4504 UGCUAUGCCAACAUAUU GCCAU (SEQ ID No: 48) ATGGCAATATGTTGGCA TAGCA (SEQ ID No: 34) down-regulated hsa-miR-214-5P MIMAT000 4564 UGCCUGUCUACACUUGC UGUGC (SEQ ID No: 49) GCACAGCAAGTGTAGAC AGGCA (SEQ ID No: 35) down-regulated hsa-miR-1185-5p MIMAT000 5798 AGAGGAUACCCUUUGUA UGUU (SEQ ID No: 50) AACATACAAAGGGTATC CTCT (SEQ ID No: 36) down-regulated hsa-miR-483-5p MIMAT000 4761 AAGACGGGAGGAAAGAA GGGAG (SEQ ID No: 51) CTCCCTTCTTTCCTCCCG TCTT (SEQ ID No: 37) down-regulated hsa-miR-365a-3p MIMAT000 9199 AGGGACUUUUGGGGGCA GAUGUG (SEQ ID No: 52) CACATCTGCCCCCAAAA GTCCCT (SEQ ID No: 38) down-regulated hsa-miR-127-3p MIMAT000 0446 UCGGAUCCGUCUGAGCU UGGCU (SEQ ID No: 53) AGCCAAGCTCAGACGGA TCCGA (SEQ ID No: 39) down-regulated hsa-miR-574-3p MIMAT000 3239 CACGCUCAUGCACACACC CACA (SEQ ID No: 54) TGTGGGTGTGTGCATGA GCGTG (SEQ ID No: 40) down-regulated hsa-miR-125b-5p MIMAT000 0423 UCCCUGAGACCCUAACU UGUGA (SEQ ID No: 55) TCACAAGTTAGGGTCTC AGGGA (SEQ ID No: 41)

[0302] Based on this list, the inventors then shortlisted 16 microRNAs most likely to be those used in the construction of the microRNA-detector, as shown in Table 2 below.

TABLE-US-00078 Expression in T-ALL microRNA ID Accession Number Sequence Target sequence up-regulated hsa-miR-3687 MIMAT0018115 CCCGGACAGGCGUUCGUG CGACGU (SEQ ID No: 67) ACGTCGCACGAACGCCTGT CCGGG (SEQ ID No: 56) up-regulated hsa-miR-92a-2-5p MIMAT00045o8 GGGUGGGGAUUUGUUGC AUUAC (SEQ ID No: 68) GTAATGCAACAAATCCCCA CCC (SEQ ID No: 57) up-regulated hsa-miR-20b-3p MIMAT0004752 ACUGUAGUAUGGGCACU UCCAG (SEQ ID No: 69) CTGGAAGTGCCCATACTAC AGT (SEQ ID No: 58) up-regulated hsa-miR-6087 MIMAT0023712 UGAGGCGGGGGGGCGAG C (SEQ ID No: 70) GCTCGCCCCCCCGCCTCA (SEQ ID No: 59) up-regulated hsa-miR-106a-3p MIMAT0004517 CUGCAAUGUAAGCACUUC UUAC (SEQ ID No: 71) GTAAGAAGTGCTTACATTG CAG (SEQ ID No: 60) up-regulated hsa-miR-7704 MIMAT0030019 CGGGGUCGGCGGCGACGU G (SEQ ID No: 72) CACGTCGCCGCCGACCCCG (SEQ ID No: 61) down-regulated hsa-miR-539-5p MIMAT0003163 GGAGAAAUUAUCCUUGG UGUGU (SEQ ID No: 42) ACACACCAAGGATAATTTC TCC (SEQ ID No: 28) down-regulated hsa-miR-487a-3p MIMAT0002178 AAUCAUACAGGGACAUCC AGUU (SEQ ID No: 43) AACTGGATGTCCCTGTATG ATT (SEQ ID No: 29) down-regulated hsa-miR-655-3p MIMAT0003331 AUAAUACAUGGUUAACCU CUUU (SEQ ID No: 44) AAAGAGGTTAACCATGTAT TAT (SEQ ID No: 30) down-regulated hsa-miR-411-3p MIMAT0004813 UAUGUAACACGGUCCACU AACC (SEQ ID No: 45) GGTTAGTGGACCGTGTTAC ATA (SEQ ID No: 31) down-regulated hsa-miR-377-5p MlMAT0004689 AGAGGUUGCCCUUGGUG AAUUC (SEQ ID No: 46) GAATTCACCAAGGGCAACC TCT (SEQ ID No: 32) down-regulated hsa-miR-337-5p MIMAT0004695 GAACGGCUUCAUACAGGA GUU (SEQ ID No: 47) AACTCCTGTATGAAGCCGT TC (SEQ ID No: 33) down-regulated hsa-miR-31-3p MlMAT0004504 UGCUAUGCCAACAUAUUG CCAU (SEQ ID No: 48) ATGGCAATATGTTGGCATA GCA (SEQ ID No: 34) down-regulated hsa-miR-214-5p MIMAT0004564 UGCCUGUCUACACUUGCU GUGC (SEQ ID No: 49) GCACAGCAAGTGTAGACAG GCA (SEQ ID No: 35) down-regulated hsa-miR-1185-5p MIMAT0005798 AGAGGAUACCCUUUGUA UGUU (SEQ ID No: 50) AACATACAAAGGGTATCCT CT (SEQ ID No: 36) down-regulated hsa-miR-483-5p MIMAT0004761 AAGACGGGAGGAAAGAAG GGAG (SEQ ID No: 51) CTCCCTTCTTTCCTCCCGTC TT (SEQ ID No: 37)

Validation of MicroRNA Expression Profile

[0303] The validation of the T-ALL-specific microRNA expression profile was performed by real-time PCR quantification of each microRNA expression, using TaqMan MicroRNA assays (Applied Biosystems). MicroRNA expression was analyzed in T-ALL cell lines corresponding to different differentiation stages (Jurkat, DND4.1, MOLT4, CEM, SUP-T1, HPB-ALL, TALL-1, P12 and Loucy) and several non-T-ALL cell lines such as 293T, A549, MDA231, CaCO2, U2OS, HCT-116, ACHN, A498 and D458.

[0304] T-ALL cell lines were cultured in RPMI-1640 medium with L-glutamine supplemented with 10% of fetal bovine serum (FBS) and 1% penicillin/streptomycin (Pen/Strep). Non-T-ALL cell lines were cultured as follows: 293T, A549, MDA231 and CaCO.sub.2 in Dulbecco’s Modified Eagle’s medium supplemented with 10% FBS and 1% Pen/Strep; U2OS; HCT-116 in McCoy’s 5A medium with 10% FBS and 1% Pen/Strep; ACHN and A498 in Eagle’s Minimum Essential Medium with 10% FBS and 1% Pen/Strep; and D458 in Iscove’s Modified Dulbecco’s Media with 10% FBS and 1% Pen/Strep. All cell lines were kept at 37° C. in a 5% CO.sub.2 environment.

[0305] Total RNA was extracted from cells using TRIzol reagent, according to manufactures’ protocol. Next, microRNA expression quantification was performed using the Applied Biosystems TaqMan MicroRNA Reverse Transcription Kit, in combination with TaqMan miRNA Assays. This is a two-step process that starts with the reverse transcription of microRNA to cDNA using a microRNA RT specific primer. This reaction was followed by real-time PCR amplification of microRNAs, using microRNA-specific TaqMan probes. The PCR reactions were performed using Vii7 Real Time PCR system. MicroRNA expression was normalized using RNU6b and microRNA relative expression calculated using the 2.sup.-ΔΔCt method.

Technological Design of MicroRNA-Detectors

[0306] MicroRNA-detectors (i.e. the constructs of the invention) were built using the pCDH-EF1-MCS-T2A-GFP (PGK-Puro) expression vector (from SBI) as backbone, as shown in FIG. 4. This bidirectional promoter expression vector allows the expression of GFP with a constitutive EF1 promoter. In negative orientation, the PGK promoter drives the expression of the puromycin marker. For proof-of-concept purposes, GFP was used as a surrogate for the therapeutic gene.

[0307] The inventors started by introducing the Lac operon system into the vector backbone shown in FIG. 4, the bidirectional lentiviral expression vector (bdLV). This process involved:

STEP 1 - Cloning Lac Operator Sequences (LacO) Downstream of the EF1 Promoter

[0308] For this purpose, the inventors amplified the SV40 intron containing three copies of the Lac Operator sequence (SV40intron/3LacO) from the pOPI3CAT (LacSwitch II Inducible Mammalian Expression System from Agilent) and cloned it into the bdLV (bdLV_LacO). SV40intron/3LacO was amplified using primers with restriction sites for EcoRI and NotI (Table 3). Upon amplification, both PCR product and BdLV vector were digested with EcoRI and NotI restriction enzymes (Thermo Scientific). The digested SV40intron/3LacO PCR product and the BdLV vector were then ligated using T4 DNA ligase (Fermentas). The correct insertion of LacO sequences was confirmed by restriction enzyme diagnostic digestion and Sanger sequencing.

STEP 2 - Cloning the Lac Repressor (LacI) Downstream of PGK Promoter

[0309] This step involved the replacement of the puromycin by LacI (in reverse orientation). The LacI was PCR-amplified from the pCMVLacI vector (LacSwitch II Inducible Mammalian Expression System from Agilent) and sub-cloned into a smaller vector (pcDNA3.1+) to be obtained in reverse orientation. To that end LacI_NLS was amplified using primers with restriction sites for the blunt-end SmaI (Table 3). Upon purification, LacI_NLS PCR product and pcDNA3.1+ vector were digested with SmaI (from NEB). The digested LacI_NLS fragment and pcDNA3.1+ vector were then ligated using T4 DNA ligase (Fermentas). The insertion of LacI in the correct orientation was confirmed by restriction enzyme digestion and Sanger sequencing. Next, directed mutagenesis (QuickChange Lightning Site-Directed Mutagenesis kit from Agilent) was used to create the restriction enzymes sites necessary to cut out the puromycin cDNA from the bdLV_LacO vector and replace it by LacI. Because of bdLV_LacO size (approximately 10 Kb) the region of the bdLV_LacO vector to be mutated (puromycin and flanking sequences) was removed and sub-cloned into pcDNA3.1+ vector. More specifically, the restriction enzymes NotI and EcoRI were used to digest both the bdLV_LacO and pcDNA3.1+ vectors. Puromycin digestion product and digested pcDNA3.1+ were ligated using T4 DNA ligase (Fermentas). This intermediate smaller vector (approximately 6.7 Kb) was used to eliminate one XhoI restriction site and to generate an AvrII restriction site. Once mutated, puromycin and flanking regions was amplified using primers with restriction enzymes sites for HpaI and SpeI (Table 3) and cloned back into bdLV vector upon ligation of the PCR product and vector digested with those enzymes. Puromycin was then removed from bdLV_LacO vector using XhoI and AvrII restriction enzymes while, the same enzymes were used to cut out LacI from pcDNA3.1+ vector_LacI. T4 DNA ligase was used to ligate bdLV_LacO vector and LacI, creating bdLV_LacI_LacO vector. The correct insertion of LacI in the bdLV_LacO vector was confirmed by restriction enzyme diagnostic digestion and Sanger sequencing.

[0310] Next, the inventors cloned four target sites of miR-29a, miR-149, or miR-29a and miR-149 (microRNAs specifically absent or down-regulated in T-ALL cells) downstream of the reporter gene promoter, in the bdLV_LacI_LacOconstruct. To this end, they created a restriction enzyme site for XmaI downstream of GFP. Four target sites of each microRNA (or both) were synthesized in tandem and introduced into bdLV-LacI_LacO vector upon digestion with XmaI and ligation with T4 DNA ligase.

[0311] In a second phase, the inventors cloned four target sites of miR-128a or miR-153 (microRNAs specifically up-regulated in T-ALL cells) downstream of the repressor of the reporter gene promoter, in the bdLV_LacI_LacO construct. To this end, four target sites of each microRNA were synthesized in tandem and introduced in the bdLV-LacI_LacO vector upon digestion with the restriction enzyme XhoI and ligation with the T4 DNA ligase.

[0312] References for the methods used [0313] 1) Landgraf, P. et al. (2007) Cell 29;129(7):1401-14 [0314] 2) Rosenfeld, N. et al. (2008) Nat Biotechnol Apr;26(4):462-9 [0315] 3) Fulci, V. et al. (2009) Genes, Chromosomes & Cancer 48:1069-1082 [0316] 4) de Leeuw, D. et al. (2013) Clin Cancer Res; 19(8); 2187-96 [0317] 5) Schotte, D. et al (2009) Leukemia Feb;23(2):313-22. [0318] 6) Coskum, E. et al. (2013) Leukemia Research 37:647- 656 [0319] 7) Lu, J. et al (2005) Nature. Jun 9;435 (7043):834-8 [0320] 8) Mavrakis, K.J. et al (2011) Nat Genet. Jun 5;43(7):673-8, [0321] 9) Schotte, D. et al. (2011) Haematologica 2011;96(5):703-711 [0322] 10) Sanghvi, V. R. eta al. (2014) Sci. Signal. Nov 18;7(352):ra111.

TABLE-US-00079 Primer sequences used Primer’s name Primers sequence EcoR1_LacO TGA GGC GAA TTC GTA AAT ATA AAA TTT ACT AGG - SEQ ID No: 10 NotI_LacO TAT AGC GGC CGC CTA AAA TAC ACA AAC A-SEQ ID No: 11 SmaI_LacI F TAT GCC CGG GGA GGT ACC CTC CCA CCA TG- SEQ ID No: 12 SmaI_LacI R CCA CCC GGG TCA AAC CTT CCT CTT CTT CTT AGG- SEQ ID No: 13 HpaI_pcDNA3.1 TGA GCG TTA ACT TTT AAA AGA AAA G- SEQ ID No: 14 SpeI_pcDNA3.1 TAT AAC TAG TCT CGT GCA GAT GGA CAG CAC CG- SEQ ID No: 15

Example 2 - Definition and Validation of a T-ALL-Specific miRNA Expression Profile

[0323] In order to start constructing the microRNA-detector constructs of the invention, the inventors took advantage of publicly available human datasets to establish a provisional T-ALL-specific microRNA expression profile. Using this approach, the inventors were able to identify 12 miRNAs specifically down-regulated and up-regulated in T-ALL cells.

[0324] As shown in FIG. 3, the validation of these 12 microRNAs by real-time PCR allowed them to confirm miR-128a and miR-153 as being specifically up-regulated in T-ALL cells, and miR-29a and miR-149 as being specifically down-regulated in T-ALL cells.

[0325] Subsequent bioinformatic analyses of a larger cohort of publicly available microRNA data obtained from human T-ALL cells and normal cells and tissues has identified 25 miRNAs as being specifically down-regulated (miR-539-5p, miR-487a-3p, miR-655-3p, miR-411-3p, miR-377-5p, miR-337-5p, miR-31-3p, miR-214-5p, miR-1185-5p, miR-483-5p, miR-365a-3p, miR-127-3p, miR-574-3p and miR-125b-5p) and up-regulated (miR-3687, miR-92a-2-5p, miR-20b-3p, miR-6087, miR-106a-3p, miR-7704, miR-5701, miR-766-5p, miR-3609, miR-3615 and miR-4746-5p) in T-ALL cells in comparison with healthy cells. These have been shortlisted to 16 microRNAs most likely to be used in the construction of the microRNA detector, 10 specifically down-regulated (miR-539-5p, miR-487a-3p, miR-655-3p, miR-411-3p, miR-377-5p, miR-337-5p, miR-31-3p, miR-214-5p, miR-1185-5p and miR-483-5p) and 6 specifically up-regulated (miR-3687, miR-92a-2-5p, miR-20b-3p, miR-6087, miR-106a-3p and miR-7704) in T-ALL cells.

Example 3 - Design and Construction of microRNA-Detectors/Constructs

[0326] The microRNA-detector construct developed by the inventors consists of a bidirectional lentiviral expression vector, in which the therapeutic gene is expressed by one promoter, and a repressor of the therapeutic gene promoter is expressed by the second promoter. The Lac operon system is used as the repressor. The expression of both mRNAs is regulated by T-ALL-cell-specific microRNAs. For proof-of-concept purposes, GFP was used instead of an apoptosis-inducing gene (i.e. GFP expression was used as a surrogate for the therapeutic gene).

[0327] As shown in FIG. 4, as the backbone for the detector system, the inventors used the pCDH-EF1-MCS-T2A-GFP (PGK-Puro) expression vector from SBI (referred to as BdLV). This bidirectional promoter expression vector allows the expression of GFP with a constitutive EF1 promoter. In negative orientation the PGK promoter drives the expression of the puromycin marker.

[0328] The inventors introduced a Lac operon system in the backbone vector, as shown in FIG. 5, which functioned as the repression system. The process was divided in two steps:

I) Cloning Lac Operator Sequences (LacO) Downstream of the EF1 Promoter

[0329] As shown in FIG. 6, the Lac repressor (LacI) binds to Lac Operator (LacO) regulatory sites in the promoter turning off transcription, confirming that the insertion of LacO sequences does not affect the expression of GFP by the EF1 promoter (FIG. 6A).

[0330] The inventors further confirmed that the LacO was functional. The inventors verified that LacI proteins can bind to Lac operator sequences in bdLV_LacO and repress GFP expression by the EF1 promoter. As shown in FIG. 6Bi, transfection of a LacI expression vector in bdLV_LacO expressing cells resulted in decreased GFP expression. The inventors further confirmed the ability of LacO to repress EF1 promoter by treating cells co-transfected with LacI and bdLV_LacO vectors with Isopropyl β-D-1-thiogalactopyranoside (IPTG) for 24 and 48h. IPTG binds to and represses LacI. Thus, the increase in GFP expression observed when cells are treated with IPTG shows that in the absence of IPTG, LacI binds to Lac operator sequences repressing GFP transcription by the EF1 promoter (FIG. 6Bii).

Ii) Cloning of the Lac Repressor (LacI) Downstream of PGK Promoter

[0331] This step involved the replacement of the puromycin by LacI (in reverse orientation). The LacI was PCR-amplified from the pCMVLac vector (LacSwitch II Inducible Mammalian Expression System from Agilent) and sub-cloned into a smaller vector (pCDN3.1+) to be expressed in the reverse orientation. Next, directed mutagenesis was used to create the restriction enzymes sites necessary to cut out the puromycin cDNA from the bdLV_LacO vector and replace it by LacI.

[0332] As shown in FIG. 7, the inventors confirmed that the LacI proteins expressed by the PGK promoter were functional, binding to the Lac operator sequences in bdLV_LacI_LacOand repressing GFP expression by the EF1 promoter. To this end, cells transfected with the bdLV_LacI_LacO vector were treated with IPTG. If the LacI proteins expressed by PGK are functional, treatment with IPTG should increase GFP expression. The inventors observed that treatment with IPTG de-repressed GFP expression in about 50%.

[0333] The inventors then cloned four target sites of miR-29a, miR-149, or miR-29a and miR-149 (microRNAs specifically absent or down-regulated in T-ALL cells) downstream of the reporter gene promoter, in the bdLV_LacI_LacO construct, as shown in FIG. 8A. In a second phase, the inventors cloned four target sites of miR-128a or miR-153 (microRNAs specifically up-regulated in T-ALL cells) downstream of the repressor of the reporter gene promoter, in the bdLV_LacI_LacO construct, as shown in FIG. 8B.

Example 4 - Testing of the MicroRNA-Detector Efficiency and Specificity in Vitro

[0334] To evaluate the actual efficiency and specificity of the different microRNA-detectors to selectively target leukemia cells in vitro, the inventors started by performing cultures of T-ALL (‘A’ of FIGS. 9A and 9B) or non-T-ALL (‘B’ of FIGS. 9A and 9B) cells, transduced with the microRNA-detectors BdLV_miR29a_4xT, BdLV_miR149_4xT, and BdLV_miR29a_4xT_miR149_4xT.

[0335] Flow cytometry analysis of GFP expression enabled the inventors to determine the efficiency and specificity of each microRNA-detector tested (see FIGS. 9A and 9B). The results show that in cells expressing miR29a or miR149, the microRNA-detector BdLV_miR29a_4xT and BdLV_miR149_4xT (respectively) efficiently repress the expression of the reporter gene (up to 90% of GFP expression repression as compared with BdLV_LacI_LacO transduced cells) (see FIGS. 9A and B). In cells not expressing any of these microRNAs, transduction with the respective microRNA-detector did not affect GFP expression (‘A’ of FIGS. 9A and 9B). Importantly, in cells expressing both miR29a and miR149, transduction with the BdLV_miR29a_4xT_miR149_4xT detector has an additive effect, inducing a repressive effect on GFP expression higher than the detectors BdLV_miR29a_4xT and BdLV_miR149_4xT (‘B’ of FIGS. 9A and 9B).

[0336] Referring now to FIGS. 10A and 10B, the inventors then performed cultures of T-ALL cells transduced with the microRNA-detectors BdLV_miR128_4xT,BdLV_miR153_4xT and BdLV_miR128_4xT_miR153_4xT. Flow cytometry analysis of GFP expression showed that in T-ALL cells expressing miR128 and miR153, the microRNA-detector BdLV_miR128_4xT, BdLV_miR153_4xT and BdLV_miR128_4xT_miR153_4xT efficiently de-repressed the expression of the reporter gene (up to a 40 fold increase in GFP expression as compared with BdLV_LacI_LacO transduced cells) (see FIGS. 10A and 10B).

[0337] Referring now to FIG. 11, the inventors performed cultures of cells transduced with microRNA-detectors regulated by microRNAs present or up-regulated and absent or down-regulated. As shown, in 293-T non-T-ALL cells that do not express the microRNAs 128 and 153, transduction with the microRNA-detectors BdLV_miR128_4xT_miR29a_4xT, BdLV_miR128_4xT_miR149_4xT, BdLV_miR128_4xT_miR29a_4xT_miR149_4xT and BdLV_miR153_4xT_miR29a_4xT_miR149_4xT resulted in the efficient repression of the reporter gene (up to 90% of GFP expression repression as compared with BdLV_LacI_LacO transduced cells in the microRNA-detectors containing both miR29a and 149 target sites).

[0338] As for the CEM T-ALL cells that express miR-128, miR-153 and miR-29a, transduction with the microRNA-detectors BdLV_miR128_4xT_miR29a_4xT, BdLV_miR128_4xT_miR29a_4xT_miR149_4xT and BdLV_miR153_4xT_miR29a_4xT_ miR149_4xT resulted in the efficient repression of the reporter gene. Conversely, transduction with the construct BdLV_miR128_4xT_miR149_4xT, had a small effect on reporter gene expression.

[0339] Referring to FIG. 12, in 293-T non-T-ALL cells that do not express the microRNAs 128 and 153, transduction with the microRNA-detectors BdLV_miR-153_4xT-miR-29a_4xT_miR-149_4xT, BdLV_miR-128_4xT-miR-29a_4xT_miR-149_4xT and BdLV miR-128_4xT _miR-153_4xT-miR-29a_4xT_miR-149_4xT resulted in the efficient repression of the reporter gene.

[0340] In the DND4.1 T-ALL cells expressing the microRNAs 128 and 153, transduction with the microRNA-detectors BdLV_miR-153_4xT-miR-29a_4xT, BdLV_miR-153_4xT-miR-149_4xT, and BdLV_miR-128_4xT_miR-153_4xT-miR-149_4xT efficiently de-repressed the expression of the reporter gene. As for the CEM T-ALL cells that express miR-128, miR-153 and miR-29a, transduction with the microRNA-detectors BdLV_miR-128_4xT-miR-149_4xT, BdLV_miR-153_4xT-miR-149_4xT and BdLV_miR-128_4xT miR-153_4xT-miR-149_4xT resulted in the efficient de-repression of the reporter gene.

[0341] Referring now to FIG. 13, the inventors then performed cultures of T-ALL and non-T-ALL cells transduced with non-integrative lentiviral vectors. As illustrated, in 293-T non-T-ALL cells that do not express the microRNAs 128 and 153, transduction with all of the microRNA-detectors resulted in the efficient repression of the reporter gene. In contrast, in CEM T-ALL cells, transduction with the microRNA-detectors miR-153_4xT-miR-29a_4xT and miR-153_4xT-miR-149_4xT resulted in the efficient de-repression of the reporter gene.

Discussion & Conclusions

[0342] The inventors have generated compelling proof-of-concept data for the feasibility and effectiveness of microRNA-detectors to modulate GFP expression exclusively in T-ALL cells as a practical example of regulation of the activity of an effector gene in the first nucleic acid sequence encoding a therapeutically active molecule or a reporter molecule of the first aspect of the present invention. The inventors anticipate that such a system can be adapted in the future to other cancer types, or even other disease types, with the introduction of the relevant microRNA target sequences to the cancer or disease of interest, thereby paving the way to the use of this gene therapy technology in any disease in which cells display a varied miRNA profile.

[0343] The intrinsic ability of this system to distinguish between the identities of a T-ALL cell and that of a non-T-ALL cell within the body of the patient is, hence, a hallmark of the technology and a critically valuable tool in precision oncology. It provides the significant advantage over competing gene therapy technologies developed to date which are applied to precision oncology and it has been deliberately designed to provide the best possible efficacy and safety outcomes for patients. This innovative technology has the potential to effectively circumvent the lack of specificity in T-ALL therapy. Importantly, it serves as a proof-of-concept that this strategy can be applied to the development of similar personalized therapies in other diseases and cancer cell types. In addition, the technology can be effectively use in diagnosis of certain conditions which are characterised by a varied miRNA profile in a disease cell or tissue compared to a healthy cell/tissue.

[0344] Finally, with the system of the invention, a therapeutic molecule can be delivered with high specificity and efficiency using just one single vector, and it does not require induction with external factors or cues. Moreover, co-localisation of the encoded molecules in the same cell is achieved at lower dosages than would be possible using a multiple construct approach. As such, this results in a much simpler system that is therefore significantly advantageous over previous technologies.

REFERENCES

[0345] 1) Martini, M., Vecchione, L., Siena, S., Tejpar, S., Bardelli, A. (2011) Targeted therapies: how personal should we go. Nature Reviews of Clinical Oncology. Nov 15;9(2):87-97.

[0346] 2) Pui, C .H., Relling, M.V., Downing, J.R. (2004) Acute lymphoblastic leukemia. New England Journal of Medicine. Apr 8;350(15):1535-48.

[0347] 3) Fullmer, A., O’Brien, S., Kantarjian, H., Jabbour, E. (2009) Novel therapies for relapsed acute lymphoblastic leukemia. Curr Hematol Malig Rep. Jul;4(3):148-56.

[0348] 4) Smith, M. A. Update on developmental therapeutics for acute lymphoblastic leukemia (2009)C urr Hematol Malig Rep. 2009 Jul;4(3):175-82.

[0349] 5) Bartel, D.P. (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell Jan 23;116(2):281-97.

[0350] 6) Huntzinger, E., Izaurralde, E. (2011) Gene silencing by microRNAs: contributions of translational repression and mRNA decay. Nat Rev Genet Feb;12(2):99-110.

[0351] 7) Kasinski, A.L., Slack, F.J. (2011) Epigenetics and genetics. MicroRNAs en route to the clinic: progress in validating and targeting microRNAs for cancer therapy. Nat. Rev. C ancer Nov 24;11(12):849-64.

[0352] 8) Rosenfeld, N., Aharonov, R., Meiri, E., Rosenwald, S., Spector, Y., Zepeniuk, M., Benjamin, H., Shabes, N., Tabak, S., Levy, A., Lebanony, D., Goren, Y., Silberschein, E., Targan, N., Ben-Ari, A., Gilad, S., Sion-Vardy, N., Tobar, A., Feinmesser, M., Kharenko O, Nativ O, Nass D, Perelman M, Yosepovich A, Shalmon B, Polak-C harcon S, Fridman E, Avniel A, Bentwich I, Bentwich Z, C ohen D, C hajut A, Barshack I. (2008) MicroRNAs accurately identify cancer tissue origin. Nat Biotechnol Apr;26(4):462-9.

[0353] 9) Landgraf, P., Rusu, M., Sheridan, R., Sewer, A., Iovino, N., Aravin, A., Pfeffer, S., Rice, A., Kamphorst, A.O., Landthaler, M., Lin, C., Socci, N.D., Hermida, L., Fulci, V., Chiaretti, S., Foà, R., Schliwka, J., Fuchs, U., Novosel, A., Müller, R.U., Schermer, B., Bissels, U., Inman, J., Phan, Q., Chien, M., Weir, D.B., Choksi, R. et al. (2007) A mammalian microRNA expression atlas based on small RNA library sequencing. Cell Jun 29;129(7):1401-14.

[0354] 10) Brown, B.D., Venneri, M.A., Zingale, A., Sergi Sergi, L., Naldini, L. (2006) Endogenous microRNA regulation suppresses transgene expression in hematopoietic lineages and enables stable gene transfer. Nat Med May;12(5):585-91.

[0355] 11) Gentner, B., Visigalli, I., Hiramatsu, H., Lechman, E., Ungari, S., Giustacchini, A., Schira, G., Amendola, M., Quattrini, A., Martino, S., Orlacchio, A., Dick, J.E., Biffi, A., Naldini, L. (2010) Identification of hematopoietic stem cell-specific miRNAs enables gene therapy of globoid cell leukodystrophy. Sci Transl Med. Nov 17;2(58):58ra84

[0356] 12) Xie, J., Xie, Q., Zhang, H., Ameres, S.L., Hung, J.H., Su, Q., He, R., Mu, X., Seher Ahmed, S., Park, S., Kato, H., Li, C., Mueller, C., Mello, C.C., Weng, Z., Flotte, T.R., Zamore, P.D., Gao, G. (2011) MicroRNA-regulated, systemically delivered rAAV9: a step closer to CNS-restricted transgene expression. Mol Ther. Mar;19(3):526-35.

[0357] 13) Skalsky, R.L., Cullen, B.R. (2011) Reduced expression of brain-enriched microRNAs in glioblastomas permits targeted regulation of a cell death gene. PLoS One 6(9):e24248.

[0358] 14) Garzon, R., Fabbri, M., Cimmino, A., Calin, G.A., Croce, C.M. (2006) MicroRNA expression and function in cancer. Trends Mol Med. Dec;12(12):580-7.

[0359] 15) Lu, J., Getz, G., Miska, E.A., Alvarez-Saavedra, E., Lamb, J., Peck, D., Sweet- Cordero, A., Ebert, B.L., Mak, R.H., Ferrando, A.A., Downing, J.R., Jacks, T., Horvitz, H.R., Golub, T.R. (2005) MicroRNA expression profiles classify human cancers. Nature. Jun 9;435(7043):834-8.

[0360] 16) Mavrakis, K.J., Van Der Meulen, J., Wolfe, A.L., Liu, X., Mets, E., Taghon, T., Khan, A.A., Setty, M., Rondou, P., Vandenberghe, P., Delabesse, E., Benoit, Y., Socci, N.B., Leslie, C .S., Van Vlierberghe, P., Speleman, F., Wendel, H.G. (2011) A cooperative microRNA tumor suppressor gene network in acute T-cell lymphoblastic leukemia (T-ALL). Nat Genet. 2011 Jun 5;43(7):673-8.

[0361] 17) Schotte, D., C hau, J.C ., Sylvester, G., Liu, G., C hen, C ., van der Velden, V.H., Broekhuis, M.J., Peters, T.C ., Pieters, R., den Boer, M.L. (2009) Identification of new microRNA genes and aberrant microRNA profiles in childhood acute lymphoblastic leukemia. Leukemia Feb;23(2):313-22.

[0362] 18) Silva, A., Laranjeira, A.B., Martins, L.R., C ardoso, B.A., Demengeot, J., Yunes, J.A., Seddon, B., Barata, J.T. (2011) IL-7 contributes to the progression of human T-cell acute lymphoblastic leukemias. Cancer Res. Jul 15;71(14):4780-9.