USE OF TROP-2 AS PREDICTIVE MARKER OF RESPONSE TO ANTI-TUMOR THERAPY BASED ON INHIBITORS OF CD9, AKT AND MOLECULES OF THE TETRASPANIN SIGNALLING NETWORK

Abstract

A method for the diagnosis and treatment of cancer is characterized by the fact that an increase in the levels of Trop-2 in the tumor, as compared to the levels of Trop-2 in the corresponding normal tissues, constitutes a biological marker that can predict the tumor response to anticancer therapy with drugs directed against components of the signalling network of Trop-2, including but not limited to drugs which inhibit CD9, Akt and molecules of the tetraspanin signalling network. More particularly, the use of the biological marker Trop-2 is disclosed in the screening of new compounds, and in the clinical setting as an indicator for the use of anticancer drugs targeted against molecules of the signalling network of Trop-2, including but not limited to drugs that inhibit CD9, Akt and molecules of the tetraspanin signalling network.

Claims

1. Method to predict in vitro the outcome of an anticancer therapy with drugs inhibiting the activity of components of the Trop-2 signaling network, wherein said components are selected from the group consisting of CD9, Akt and molecules of the tetraspanin signalling network, said method comprising or consisting of determining the expression levels of Trop-2 protein or of the corresponding mR A in a biological sample, an effective outcome occurring when an increase of the expression levels of Trop-2 protein or of the corresponding mRNA as compared to the levels in the corresponding normal tissues is detected.

2. Method according to claim 1, wherein the increase in the mRNA of Trop-2 in the tumor tissues compared to the corresponding normal tissues is equal to or greater than 10%, as quantified by means of RT-PCR or real time quantitative RT-PCR.

3. Method according to claim 1, wherein the increase in the Trop-2 protein in the tumor tissues compared to the corresponding normal tissues is equal to or greater than 10%, as quantified by means of immunohistochemistry, ELISA assays, Western blotting.

4. Method for in vitro screening of candidate drugs for the treatment or prevention of cancer, or the inhibition of cancer cell growth, wherein such drugs are directed against components of the Trop-2 signaling network, wherein said components are selected from the group consisting of CD9, Akt and molecules of the tetraspanin signalling network , said method comprising or consisting of the following steps: a. administering the compound to be tested, in sterile saline solution, to cells expressing Trop-2 and not expressing Trop-2, wherein the non-expressing cells act as a control of specificity; in parallel administering the sterile saline solution alone to cells expressing Trop-2 and not expressing Trop-2 (untreated controls), wherein the sterile saline solution alone acts as a control of activity; b. detecting the biological activity of the compound of step (a) on cells expressing Trop-2 in comparison with treated controls not expressing Trop-2 and untreated controls expressing and not expressing Trop-2, in which the biological activity is a reduction of cell proliferation in cells expressing Trop-2 compared to treated control cells not expressing Trop-2 and compared to untreated control cells expressing and not expressing Trop-2; c. selecting the compound of step (a) that reduces cell proliferation by at least 10% in treated cells expressing Trop-2, in comparison with cell proliferation in treated cells not expressing Trop-2 and in untreated cells expressing and not expressing Trop-2.

5. Compound inhibiting the activity of components of the Trop-2 signaling network, wherein said components are selected from the group consisting of CD9, Akt and molecules of the tetraspanin signalling network , for use in the treatment of tumors expressing levels of Trop-2 protein or corresponding mRNA higher than normal tissue.

6. Compound according to claim 5, wherein said compound is chosen from the group consisting of oligonuclotides, engineered molecules corresponding to CD9, Akt and molecules of the tetraspanin signalling network which act as “dominant negative” molecules, monoclonal antibodies, pharmacological inhibitors, small-molecule chemical compounds or combination thereof.

7. Compound according to claim 5, wherein said compound is chosen from the group consisting of MK-2206, A6730, Perifosine, GSK690693, GSK21 10183, GDC-0068, AT7867, ARQ092, AZD5363, A-674563, PHT-427, PF-04691502, SureCN 1078972, 842148-40-7, AC1NX3D3, MLS002702033, SureCNl 0005574, SureCNl 559590, SureCN570829, SH-5, SH-6, Honokiol, Miltefosine, Triciribine phosphate (Akt inhibitors), K00598a, DAPH 2, SureCN238877 (EGFR inhibitors), SureCN4269573 (inhibitor of EGFR, c-RAF, Src), dasatinib (Src inhibitor), SureCN1518805, 1,9-Pyrazoloanthrone, AS-601245, aminopyridine deriv. 2 (JNK inhibitors).

8. Compound according to claim 5, in combination with drugs chosen from the group consisting of chemotherapic drugs, alkylating agents, antimetabolites, anti-tumor antibiotics, topoisomerase inhibitors, mitotic inhibitors, corticosteroids, differentiating agents, hormone therapy, targeted kinase inhibitors, the proteosome inhibitor bortezomib.

9. Compound according to claim 5, wherein said molecules of the tetraspanin signaling network are selected from the group consisting of the epidermal growth factor receptor (EGFR), the tyrosine-protein kinase Met, the serine/threonine-protein kinase c-RAF, the proto-oncogene tyrosine-protein kinase Src, the small GTP binding protein CDC42, the tyrosine-protein kinase JAK2, the cAMP-dependent protein kinase catalytic subunit alpha (PKA C-alpha), the tyrosine-protein phosphatase non-receptor type 11 (SHP2), the insulin receptor substrate 1 (IRS1), the serine/threonine-protein kinase PAK 1, the mitogen-activated protein kinase 8 (JNK).

10. Method for the in vivo screening of candidate drugs for the treatment or prevention of cancer, or the inhibition of cancer cell growth, wherein such drugs are directed against components of the signalling network of Trop-2, including CD9, Akt and molecules of the tetraspanin signalling network, said method comprising the steps of: a. administering the compound to be tested, directed against components of the signalling network of Trop-2, including CD9, Akt and molecules of the tetraspanin signalling network, in sterile saline solution, to tumors which are positive or negative for the Trop-2 biological marker according to claim no. 1, in pre-clinical and clinical models, where the negative tumors act as a control of specificity; in parallel administering the sterile saline solution alone to tumors which are positive or negative for the Trop-2 biological marker (untreated controls), where the sterile saline solution alone acts as a control of activity, b. detecting the biological activity of the compound of step (a) on tumors which are positive for the Trop-2 biological marker, in comparison with treated controls negative for the Trop-2 biological marker and untreated controls positive and negative for the Trop-2 biological marker, where the biological activity is a reduction of tumor growth in tumors positive for the Trop-2 biological marker compared to control tumors negative for the Trop-2 biological marker and compared to untreated control tumors positive and negative for the Trop-2 biological marker; c. selecting the compound of step (a) that reduces tumor growth by at least 10% in tumors which are positive for the Trop-2 biological marker, in comparison with treated control tumors negative for the Trop-2 biological marker and untreated control tumors positive and negative for the Trop-2 biological marker.

Description

DESCRIPTION OF THE DRAWINGS

[0044] FIG. 1. Trop-2 cytoplasmic tail determinants responsible for growth stimulation. (a) Secondary structure prediction of the C-terminal portion of Trop-2 (aa 275-323); negatively-charged amino acids are underlined. The prediction softwares which were used are indicated on the left. h (highlighted in dark gray): α-helix, e (highlighted in black): ß-strand; c (highlighted in light gray): connecting region (loop). Consensus secondary structure according to the prediction is indicated at the bottom, with residue-by-residue scores from a 1 to 10 scale. Prediction accuracy score is ≥80% (cubic.bioc.columbia.edu). (b) Sequence of the Trop-2 cytoplasmic tail mutants; the normal sequence (wt) is shown at the top. The HIKE domain is highlighted in the gray box; the position of the putative serine phosphorylation sites is highlighted in white. S303A, S322A: point mutations with change of serines 303 and 322, respectively, to alanine; E.fwdarw.K: point mutations with change of glutamic acids 310, 313, 316 and 320 in lysines; ΔHIKE: deletion of the HIKE region; Δcyto: deletion the entire cytoplasmic tail. (c) Effect of the Trop-2 cytoplasmic tail mutations on Trop-2 dependent growth. Growth curves of MTE 4-14 cells transfected with the empty vector or with wt Trop-2 or mutant Trop-2 as indicated. Difference between wt and mutant Trop-2: P<0.0001 (two-way ANOVA). Stars indicate statistically significant differences for individual time points (Bonferroni test for multiple comparisons): **** ≤0.0001. Bars: standard error of the mean.

[0045] FIG. 2: Trop-2 signalling clusters. Electron microscopy analysis of Trop-2 expression. (a) MCF7 breast cancer cells stained with anti Trop-2 antibodies conjugated to gold nanospheres (black dots). Trop-2 is identified in elongated villar projection and macrovilli (arrowheads) and in discrete membrane domains. White circles (30 nm in diameter) are centered on individual gold particles and encompass the areas with the highest probability to find antibody molecules bound to Trop-2. Bar: 50 nm. (b) Trop-2-expressing cells stained with anti-Trop-2 antibodies conjugated to immuno-peroxidase (dark granular deposits). Trop-2-transfected 293 cells (i), OVCA-432 ovarian cancer cells (ii), MCF-7 breast cancer cells (iii). Trop-2 is localized in discrete membrane domains (arrowheads), at a cell-cell contact (i inset: magnified contact area), in villar projections (ii) and in discrete membrane domains (iii). The presence of Trop-2 is also detected at the level of intracytoplasmic vesicles (arrows).

[0046] FIG. 3. Interaction of Trop-2 and PKCα with tetraspanin molecules and CD9. (a-d) Confocal microscopy analysis of intact cell membranes (a), membrane areas showing co-capping (b), footprints of cell membranes (c, d) of MTE 4-14 cells transfected with Trop-2 (a-c, d top) or with the empty vector (d bottom) stained simultaneously with anti-Trop-2 and anti-CD9 (member of tetraspanin webs) or anti-caveolin (negative control) (a-c) or anti-CD9 and anti PKCα (d) conjugated with fluorescent molecules. Areas of colocalization are indicated by arrowheads. (e) Co-immunoprecipitation (IP) of Trop-2, PKCα, CD9 and tetraspanins. Immunoprecipitation was performed using primary antibodies against murine CD9, CD81 and CD151 (MTE 4-14cells) or human CD9, CD82 and CD151 (MCF7 cells); the presence of Trop-2 and PKCα in immunoprecipites was detected by Western blot. IP with anti-Trop-2: positive control. (f) Trop-2/cholesterol association. Release of Trop-2 in the culture medium after treatment with methyl-β-cyclodextrin (MβCD) (left). Precipitation of Trop-2 with digitonin from BRIJ lysate (right). The treatments were performed on MTE4-14 cells transfected with Trop-2, and the presence of Trop-2 in the soluble and insoluble fractions was assessed by Western blot.

[0047] FIG. 4. The Trop-2 proteome. (a) Amount and phosphorylation of signaling molecules in MTE 4-14 transfectants, measured by Western blot. V: vector alone; T2: Trop-2. The panels with four bands show two pairs of independent measurements. (b) 2D gels of protein extracts from MTE 4-14 cells transfected with the vector alone (left) or Trop-2 (right); circles indicate proteins repressed (R, left) or induced (I, right) by Trop-2 expression.

[0048] FIG. 5. Trop-2 signalling network. (a) Network of protein-protein interactions driven by Trop-2 (SNOW analysis). Circles: all the proteins modulated by Trop-2 that can physically interact with each other (114 of the 165 proteins identified). Rectangles: “connectors” between two proteins. Lines (“edges”) represent protein-protein contacts. (b) Cancer signaling network drived by Trop-2. The proteins modulated by Trop-2 (in black) were mapped using the program Ingenuity Pathway Analysis. Hexagons: kinases; trapezoids: small G proteins and their interactors; rectangles: apoptotic factors; ovals: transcription factors/chromatin remodelling proteins; double circles: protein complexes. Highlighted in gray are signalling molecules which are not proteins. Thick gray lines: cell membrane; gray boxes: nuclear and mitochondrial compartments. P=6.19×10−45.

[0049] FIG. 6. Control of Akt signalling network by Trop-2. (a) Map of the Trop-2/Akt signalling network. The proteins which are modulated by Trop-2 (in black) were mapped using the Ingenuity Pathway Analysis software. Hexagons: kinases; rectangles: apoptotic factors; diamonds: phosphatases; ovals: transcription factors/chromatin remodelling proteins; double circles: protein complexes. Highlighted in gray are signalling molecules which are not proteins. Thick gray line: the cell membrane. (b) Modulation of the phosphorylation levels at Akt threonine 308 and serine 473 by Trop-2. Western blot analysis of MTE 4-14 cells transfected with the vector alone or with Trop-2, in the presence or absence of PMA; for each band is indicated the intensity, normalized with respect to the control.

[0050] FIG. 7. Trop-2 dictates sensitivity to CD9 inhibitors. (a, b) Control of the efficiency of CD9 silencing in MTE4-14/vector and MTE4-14/Trop-2. (a) Measurement by quantitative real-time RT-PCR of the mRNA levels of CD9 24 hours after transfection with an ineffective siRNA (control) or the specific anti-CD9 siRNA. Bars: standard deviation of the measurements. (b) Flow cytometry analysis of CD9 levels 48 hours after transfection with an ineffective siRNA (control) or the specific anti-CD9 siRNA. White profiles: control antibody, unstained; gray profiles: anti-CD9 antibody conjugated to Alexa-488. (c) Flow cytometry analysis of CD9 levels in murine or human cells stably transfected with Trop-2 (MTE 4-14/Trop-2, IGROV/Trop-2, KM12-SM/Trop-2) or endogenously expressing Trop-2 (HCT116U5.5, MCF7, HT29). White profiles: control antibody, unstained; gray profiles: anti-CD9 antibody conjugated to Alexa-488. (d) Growth curves of MTE4-14/vector (left) and MTE 4-14/Trop-2 (right) transfected with an ineffective siRNA (control) or the specific anti-CD9 or anti-Trop-2 siRNA. Bars: standard error of the mean.

[0051] FIG. 8. Trop-2 dictates sensitivity to Akt inhibitors. Growth curves of MTE 4-14 cells transfected with the vector alone or with Trop-2 and treated with ineffective siRNA (control) or specific anti-AKT siRNA (left), or with solvent alone or pharmacological inhibitors of Akt (center, right), using a dose of 400 nM or different doses as indicated. Bars: standard error of the mean.

[0052] FIG. 9. Inhibition of growth of Trop-2 expressing tumors, through inhibition of Akt. In vivo growth curves of Colo205 colon cancer cells (top) or MTE 4-14 cells transfected with Trop-2 (bottom) treated with the solvent alone or with the MK-2206 pharmacological inhibitor of Akt. MTE 4-14 control cells transfected with the empty vector does not have tumorigenic ability in this model. Difference between control and treated tumors: P<0.0001 (two-way ANOVA). Stars indicate statistically significant differences for individual time points (Bonferroni adjustment for multiple comparisons): *≤0.05, **≤0.01, ***≤0.001≤0.001 ****. Bars: standard error of the mean. Insets, flow cytometry analysis of Trop-2 expression in tumor cells and transfectants: white profiles, control antibody, unstained; gray profiles, anti-Trop-2 conjugated to Alexa-488

EXAMPLES

[0053] Cell Cultures

[0054] The human MCF-7 and OVCA-432 cell lines were grown in RPMI 1640 medium (GibcoBRL, Paisley, Scotland). The human 293 and KM12SC and the murine immortalised MTE 4-14 (Naquet, Lepesant et al. 1989) and L cell lines were maintained in DMEM. All media were supplemented with 10% fetal bovine serum (GibcoBRL), with 100 IU/ml penicillin and 100 μg/ml streptomycin (Euroclone, Milano, Italy).

[0055] DNA Transfection

[0056] Cells were transfected with DNA in Lipofectamine 2000 or LTX (Invitrogen, Carlsbad, Calif.) following the manufacturer instructions. Stable transfectants were selected in G-418-containing medium.

[0057] Immunofluorescence Analysis.

[0058] Cells plated on glass coverslips were stained with the indicated antibodies conjugated with Alexa Fluor-488/546/633, or with the same unconjugated antibodies detected by a secondary antibody conjugated with Alexa Fluor-488/546/633. Cells were either stained alive, before fixation, in medium with 10% FBS, at 37° C. for 5 minutes, or stained after fixation, by incubation with the relevant antibodies in PBS at room temperature for 30 minutes. Cells were fixed with 4% paraformaldehyde in PBS for 20 min. Permeabilisation and blocking of non-specific interactions were performed with 10% FCS, 0.1% saponin. The slides were then washed in PBS and mounted to be analyzed by LSM-510 META confocal microscope (Zeiss, Oberkochen, Germany).

[0059] Cell Footprints

[0060] “Cell footprints” are membrane remnants on tissue culture dishes after detachment of cells with EDTA (Hakomori 2002). Cell treatment and immunofluorescence analyses were conducted essentially as described (Hakomori 2002).

[0061] Co-Immunoprecipitation Assays

[0062] Cells were lysed in BRIJ buffer (150 mM NaCl, 50 mM Tris-HCl, pH 7.5, 1 mM MgCl2, 1 mM CaCl2, 1% BRIJ, protease inhibitors). Cell lysates were cleared by incubation with Protein-G Sepharose (GE Healthcare, Piscataway, N.J.) at 4° C. for 1 h. Cleared lysates were incubated with primary antibodies against putative Trop-2 interactors at 4° C. for 2 h, followed by incubation with Protein G Sepharose (at 4° C., 1 h). Protein complexes were eluted from the resin with 0.1 M glycine, pH 2.5, and probed by Western blotting with specific antibodies as indicated.

[0063] Depletion and Precipitation of Cholesterol from Cell Membranes.

[0064] To deplete cell membranes of cholesterol, intact cells were washed three times in PBS to remove serum and incubated in DMEM with 10 mM methyl-β-cyclodextrin at 37° C. for 45 min. Control cells were processed in parallel in the absence of methyl-β-cyclodextrin. Samples were centrifuged at 2000 g to remove cells and cell debris. Proteins in the supernatant were precipitated in trichloroacetic acid and analysed by Western blotting.

[0065] Cells were also harvested by scraping and lysed in buffer with 1% BRIJ. The supernatant was mixed with either 1/10 (vol/vol) methanol (control) or 1/10 (vol/vol) 10% digitonin in methanol, and incubated on ice for 10 min. Cell membranes were recovered by centrifugation at 12,000 g for 15 min. The pellet was washed in cold acetone, resuspended in Laemmli buffer and analysed by Western blotting.

[0066] Immuno-Electron Microscopy.

[0067] For immuno-gold electron microscopy (EM), cells were fixed in 4% formaldehyde, 0.05% glutaraldehyde, 0.15 M HEPES, pH 7.3, for 10 min at 37° C., and post-fixed for 50 min in 4% paraformaldehyde, 0.15 M HEPES, pH 7.3 at room temperature, as described (Polishchuk, Polishchuk et al. 2000). Cationised gold, protein A-gold, and gold-conjugated anti-rabbit antibodies (10 nm colloidal gold particles) were from British BioCell (Cardiff, UK). Immunoperoxidase EM was performed as described (Brown and Farquhar 1989). Estimates of minimal labelled areas were performed assuming an average length of antibody molecules of 11 nm.

[0068] In Vitro Cell-Growth Assays.

[0069] MTE 4-14 cells transfected with the empty vector or with Trop-2 were seeded at 1.5-3×10.sup.3 cells/well in 96-well plates (five replica wells per data point). Cell numbers were quantified by the MTT colorimetric assay (Roche Molecular Biochemicals, Mannheim, Germany) or by staining with crystal violet. Cell numbers were normalised against a reference standard curve of serially diluted cell samples.

[0070] Antibodies.

[0071] Rabbit polyclonal anti-Trop-2 antisera were generated by subcutaneous immunisation with recombinant Trop-2, that had been produced in bacteria (Fornaro, Dell'Arciprete et al. 1995). Trop-2-reactive antibodies were purified by binding to recombinant Trop-2 immobilized onto NHS-Sepharose columns (Pharmaci, Uppsala, Sweden), and eluted with 0.2 M glycine, pH 2.5. The goat anti-Trop-2 polyclonal antibody AF650 was obtained from R&D Systems, Inc. (Minneapolis, Minn.). Additional antibodies directed against murine molecules were: rat monoclonal anti-CD9 (sc-18869); rabbit monoclonal anti-Akt (ser473) (D9E) (Cell Signal Technology, MA); goat polyclonal anti-CD151 (sc-18753), anti-phospho-PKCα (S657) (sc-12356), anti-Akt (sc-1618); rabbit polyclonal anti-caveolin-1 (sc-894), anti-PKCα (sc-208), anti-phospho-Akt (Thr 308) (sc-16646-R) (Santa Cruz Biotechnology, Santa Cruz, Calif.); hamster polyclonal anti-CD81 (GTX75430) (GeneText, Irvine, Calif.). Mouse monoclonal antibodies directed against corresponding human molecules were: anti-CD9 (14-0098), anti-CD98 (14-0982) (eBioscience, San Duego, Calif.), anti-CD151 (H00000977-M02) (Abnova, Taiwan, China) and anti-CD81 (TS81) (generously supplied by Dr. F. Lanza). Secondary Alexa Fluor-488/546/633 conjugated antibodies were from Invitrogen.

[0072] Pharmacological Inhibitors.

[0073] Cells were treated with 50-100-200-400 nM A6730_SIGMA (Sigma Technical Company, St Louis, Mo. 63178-9916) or with 400 nM MK-2206 (Selleck Chemicals, Houston, Tex.) to inhibit Akt. Stock solutions were prepared in DMSO and diluited in ethanol or water, with the final concentration of DMSO and ethanol never exceeding 0.1% and 1% respectively. Control cells received vehicle alone. A second treatment was performed 24 hours after seeding.

[0074] In Vivo Models: Xenografts in Athymic Nude Mice

[0075] MTE 4-14 immortalized cell line transfected with Trop-2 (Alberti, Nutini et al. 1994), or Colo205 colon cancer cells, endogenously expressing Trop-2, were injected subcutaneously (4×10.sup.6 cells/injection) into nude mice groups (8 weeks females, CD1-Foxn1 nu/nu mice (Charles River Laboratories, Calco, Lecco, Italy). MTE 4-14 cells transfected with Trop-2 were co-injected with Matrigel 1:3 vol/vol (growth factor reduced matrix, BD Biosciences, Franklin Lakes, N.J. USA). A stock solution of MK-2206 in DMSO was diluted at the time of use in apyrogenic saline solution, to a final concentration of 0.7 mg/ml, and the drug was administered intraperitoneally at a dose of 0.35 mg/mouse every day, starting from the time in which the tumors became palpable. Control group mice were treated with the vehicle alone. Mice were visually inspected every 5-7 days and the major and minor diameters of the experimental tumors were measured. The tumor volume was calculated using the formula for the volume of ellipsoid (Dxd2/2). MTE 4-14 cells transfected with the empty vector were not tumorigenic in this model. Procedures involving animals and their care were conducted in compliance with institutional guidelines, national laws and international protocols (D.L. No.116, G.U., Suppl. 40, Feb. 18, 1992; No. 8, G.U., July, 1994; UKCCCR Guidelines for the Welfare of Animals in Experimental Neoplasia; EEC Council Directive 86/609, OJ L 358. 1, Dec. 12, 1987; Guide for the Care and Use of Laboratory Animals, United States National Research Council, 1996).

[0076] Antibody-Mediated Co-Capping.

[0077] Cells were detached from culture plates using trypsin, and incubated with the primary anti-Trop-2 antibody (T16) (Alberti, Miotti et al. 1992) for 20 min on ice. After washing, cells were incubated with the secondary Alexa Fluor 488-conjugated antibody for 10 min at 37° C., to cross-link target molecules and to induce capping of the antigen-antibody complex (Levy and Shoham 2005). The ‘capped’ cells were fixed with 1% paraformaldehyde for 10 min at room temperature. The paraformaldehyde was quenched with FBS, and cells were stained with antibodies against the membrane proteins of interest.

[0078] Western Blot Analysis.

[0079] Western blotting was performed as previously described (El Sewedy, Fornaro et al. 1998). In brief, cell lysates were analyzed by electrophoresis on denaturing polyacrylamide gel (SDS-PAGE) and transfered onto nitrocellulose filters. Filters were incubated with the relevant primary antibodies (Abcam, Cambridge, UK; Santa Cruz) in TBS with 5% non-fat dried milk. Hybridized filters were washed in TBS, 0.1% Tween-20. Antibody binding was revealed by chemiluminescence (ECL, Amersham, Aylesbury, UK), using horseradish-peroxidase-conjugated anti-mouse or anti-rabbit secondary antibodies (Calbiochem, La Jolla, Calif.). Signal intensity was quantified with NIH-image 1.62, using as reference a Kodak gray-scale standards power curve (www.kodak.com).

[0080] Plasmids

[0081] The pEYFP expression vector was obtained from Clontech (Palo Alto, Calif.). A corresponding vector devoid of the coding sequence of EYFP was used to express wild-type or mutagenized Trop-2 cDNAs. The coding sequence of the wild-type human TROP2 was amplified by PCR with the forward primer 5′ GCGATTCTCG AGTCCGGTCC GCGTTCC 3′ (SEQ ID NO:13) and with the reverse primer 5′ GCGCCGGTAC CAAGCTCGGT TCCTTTC 3′(SEQ ID NO:14) and subcloned into the pEYFP-N1 vector. The expression vectors pCMV-SPORT6 and CD316 pCMV-SPORT6 were obtained from Imagenes (Berlin, Germany). The chimeric proteins between CD9 (EcoRI/BamHI), CD316 (EcoRI/AgeI) and mCherry were constructed following standard procedures.

[0082] siRNA.

[0083] Four design strategies were used, following the procedures according to: Tuschl criteria (Elbashir, Harborth et al. 2001): Invitrogen (rnaidesigner.invitrogen.com/rnaiexpress/), Whitehead Institute web site (jura.wi.mit.edu/bioc/siRNAext/) (Semizarov, Frost et al. 2003); Sonnhammer (sonnhammer.cgb.ki.se/siSearch/) (Chalk, Wahlestedt et al. 2004). The siRNAs that were chosen were the ones identified by more than one of the above methods, or considered optimal by at least one of them . The coding sequences for hairpin RNAs (shRNAs) obtained from the corresponding siRNAs (Elbashir, Harborth et al. 2001), specific for the genes of interest, have been subcloned in the pSUPER vector (Brummelkamp, Bernards et al. 2002), under the control of the promoter for the RNA polymerase-III H1 gene. CD9 inhibition was obtained by means of anti-CD9 siRNA with target sense sequence 5′ GGTAGCAAGT GCATCAAAT 3′ (SEQ ID NO:1), and antisense sequence 5′ ATTTGATGCA CTTGCTACC 3′(SEQ ID NO:2), as an example included in the following sequences for the transcription of hairpin RNA, where the target sequences in sense and antisense orientation are underlined:

TABLE-US-00006 forward (SEQ ID NO: 3) 5′ GATCCCCGGT AGCAAGTGCA TCAAATTTCA AGAGAATTTG ATGCACTTGC TACCTTTTTG GAAA 3′, reverse (SEQ ID NO: 4) 5′ AGCTTTTCCA AAAAGGTAGC AAGTGCATCA AATTCTCTTG AAATTTGATG CACTTGCTAC CGGG 3′.

[0084] The inhibition of Akt has been obtained by means of anti-AKT siRNAs with target sense sequence 5′ GCACCTTTAT TGGCTACAA 3′ (SEQ ID NO:5) and antisense sequence 5′ TTGTAGCCAA TAAAGGTGC 3′ (SEQ ID NO:6), as an example included in the following sequences for the transcription of hairpin RNA:

TABLE-US-00007 forward (SEQ ID NO: 7) 5′ GATCCCCGCA CCTTTATTGG CTACAATTCA AGAGATTGTA GCCAATAAAG GTGCTTTTTC 3′, reverse (SEQ ID NO: 8) 5′ TCGAGAAAAA GCACCTTTAT TGGCTACAAT CTCTTGAATT GTAGCCAATA AAGGTGCGGG 3′;
or target sense sequence 5′ GGAAGGTGAT TCTGGTGAA 3′ (SEQ ID NO:9), antisense sequence 5′ TTCACCAGAA TCACCTTCC 3′ (SEQ ID NO:10), as an example included in the following sequences for the transcription of hairpin RNA:

TABLE-US-00008 forward (SEQ ID NO: 11) 5′ GATCCCCGGA AGGTGATTCT GGTGAATTCA AGAGATTCAC CAGAATCACC TTCCTTTTTC 3′, reverse (SEQ ID NO: 12) 5′ TCGAGAAAAA GGAAGGTGAT TCTGGTGAAT CTCTTGAATT CACCAGAATC ACCTTCCGGG 3′.

[0085] The corresponding constructs were transiently transfected into MTE 4-14 cells, and their effect on cell proliferation was evaluated. The levels of transcripts after silencing were quantified by real-time RT-PCR. siRNAs directed against irrelevant targets were used as negative controls, chosen after thorough verification of the absence of spurious effects on cell growth. The corresponding sequences are given below; for each siRNA the corresponding gene is indicated, with the identification code according to the RefSeq database (GenBank). siRna directed against murine Co-029/Tspan8 (NM_146010.2), used as negative control for human cells, having the target sequence sense 5′CTTTCAAACC TGAGTATAA 3′ (SEQ ID NO:15), antisense 5′ TTATACTCAG GTTTGAAAG 3′ (SEQ ID NO:16), as an example included in the following sequences for the transcription of hairpin RNA:

TABLE-US-00009 forward (SEQ ID NO: 17) 5′ GATCCCCCTT TCAAACCTGA GTATAATTCA AGAGATTATA CTCAGGTTTG AAAGTTTTTG GAAA 3′, reverse (SEQ ID NO: 18) 5′ AGCTTTTCCA AAAACTTTCA AACCTGAGTA TAATCTCTTG AATTATACTC AGGTTTGAAA GGGG 3′.
siRNA directed against human CD133 (NM_006017.2), used as negative control for murine cells, having the target sequence sense 5′ CTTGACAACG TTAATAACG 3′ (SEQ ID NO:19), antisense 5′ CGTTATTAAC GTTGTCAAG 3′ (SEQ ID NO:20), as an example included in the following sequences for the transcription of hairpin RNA:

TABLE-US-00010 forward (SEQ ID NO: 21) 5′ GATCCCCCTT GACAACGTTA ATAACGTTCA AGAGACGTTA TTAACGTTGT CAAGTTTTTG GAAA 3′, reverse (SEQ ID NO: 22) 5′ AGCTTTTCCA AAAACTTGAC AACGTTAATA ACGTCTCTTG AACGTTATTA ACGTTGTCAA GGGG 3′.
siRNA directed against human CD316 (NM_052868.2), used as negative control for murine cells, having the target sequence sense 5′ TGCAGGAAGTG GTGGGAAT 3′ (SEQ ID NO:23), antisense 5′ ATTCCCACCA CTTCCTGCA 3′ (SEQ ID NO:24), as an example included in the following sequences for the transcription of hairpin RNA:

TABLE-US-00011 forward: (SEQ ID NO: 25) 5′ GATCCCCTGC AGGAAGTGGT GGGAATTTCA AGAGAATTCC CACCACTTCC TGCATTTTTG GAAA 3′, reverse (SEQ ID NO: 26) 5′ AGCTTTTCCA AAAATGCAGG AAGTGGTGGG AATTCTCTTG AAATTCCCAC CACTTCCTGC AGGG 3′.
TROP2 silencing was obtained as previously described (Trerotola, Cantanelli et al. 2013).

[0086] Mutagenesis of the Cytoplasmic Domain of Trop-2

[0087] The mutants of the cytoplasmic domain of Trop-2 were obtained by PCR with the following primers:

TABLE-US-00012 Trop-2 Δcyto forward (SEQ ID NO: 27) 5′ CTCGGATCCA CCATGGCTCG GGGCCCC 3′, reverse (SEQ ID NO: 28) 5′ CTCGAATTCC CGGTTGGTGA TCACCAG 3′. Trop-2 E.fwdarw.K forward (SEQ ID NO: 29) 5′ GCGGAATTCC GTCCGGTCCG CGTTCCT 3′, reverse (SEQ ID NO: 30) 5′ GCGTCTAGAC TACAAGCTCG GTTTCTTTCT CAACTTCCCC AGTTTCTTGA TCTTCACCTT CTTG 3′. Trop-2 ΔHIKE forward (SEQ ID NO: 31) 5′ GCGGAATTCC GTCCGGTCCG CGTTCCT 3′, reverse (SEQ ID NO: 32) 5′ GCGTCTAGAC TACAAGCTCG GTTCCTTTCT CAACTCCCCC AGTTCCTTGA TCTCCACTCT CCGGTTGGTG ATCAC 3′. Trop-2 S303A forward (SEQ ID NO: 33) 5′ CTCGGATCCA CCATGGCTCG GGGCCCC 3′, reverse (SEQ ID NO: 34) 5′ GCGTCTAGAC TACAAGCTCG GTTCCTTTCT CAACTCCCCC AGTTCCTTGA TCTCCACCTT CTTGTACTTC CCCGCCTTTC TCCGG 3′. Trop-2 S322A forward (SEQ ID NO: 35) 5′ CTCGGATCCA CCATGGCTCG GGGCCCC 3′, reverse (SEQ ID NO: 36) 5′ GCGTCTAGAC TACAAGGCCG GTTCCTTTCT CAACTCCCC 3′.
All amplified regions were completely sequenced to verify the absence of mutations induced by Taq-polymerase.

[0088] Real-Time Quantitative RT-PCR.

[0089] Total RNA from the indicated cell lines was extracted in Trizol (Invitrogen) following the manufacturer's instructions. One μg of total RNA was used for each reverse transcription (RT) reaction, using the ImProm-II Reverse Transcriptase (Promega) according to standard protocols. Real-time quantitative PCR reactions were performed using an ABI-PRISM 7900HT Sequence Detection System (PE Applied Biosystems, Foster City, Calif.) with specific primers (Hs99999905; CD9: Mm00514275_g1; B2M: Mm00437762_ml) (Applied Biosystems) and the corresponding TaqMan® (Roche) fluorescent probes, according to the manufacturer instructions (Giulietti, Overbergh et al. 2001). Each sample was assayed in triplicate and the 2.sup.−ΔΔCT method was used to calculate relative changes in gene expression (Livak and Schmittgen 2001). A more accurate base of 1.834 was used (Guerra, Trerotola et al. 2008), as 1.1 cycles are required to double the amplified material. The GAPDH and B2M housekeeping genes were used as an internal control. For each cDNA the ΔCT (CT, target gene-CT, GAPDH/B2M) was calculated: using least-squares linear regression analysis. As amplification efficiency was linear over the range of RNA amounts used, amplification curves were used to calculate cross-over point values for siRNA-treated samples. Each sample was routinely assessed for genomic DNA contamination by using non-retrotranscribed RNA as a templates for PCR reactions.

[0090] 2D Gel and Mass-Spectrometry.

[0091] A vision over the entire genome was obtained by 2D-PAGE performed as described (Swiss Institute of Bioinformatics (SIB)—http://us.expasy.org/ch2d/protocols/). The mass spectrometry analyses were performed at the University of York (www.york.ac.uk/depts/biol/tf/proteomics/).

[0092] Pathway Analysis and Identification of Trop-2 Signaling Network

[0093] The proteome of Trop-2 was analyzed using the SNOW (snow.bioinfo.cipf.es/cgi-bin/snow.cgi) and Ingenuity Pathways Analysis (IPA, Ingenuity Systems, www.ingenuity.com) bioinformatics tools. SNOW (snow.bioinfo.cipf.es/cgi-bin/snow.cgi) builds networks of protein-protein interaction, mapping the protein over a reference interactome. The reference interactome is a set of pair-wise direct protein interactions, where the nodes are the proteins themselves and the connecting edges are the interaction events. A Trop-2-dependent interactome was built using the HPRD (Human Protein Reference Database), IntAct, BIND (Biomolecular Interaction Network Database), DIP (Database of Interacting Proteins) and MINT (Molecular Interaction Database) databases. These were used to build a minimal connected network (MCN). Topological networks were evaluated on the basis of the node connections degree (i.e. number of edges of each node); the betweenness (i.e. a measure of centrality of nodes and of their distribution); the clustering coefficient distribution (i.e. the connectivity of the neighbourhood of each node); the number of components of the network (i.e. the different groups of nodes that are generated in a network analysis); the bicomponents (i.e. the number of node groups connected to another node group by a single edge) and the articulation points (i.e. the edges that join bicomponents in a network). MCNs were identified using the Dijkstra's algorithm applying a stringent option that permits the introduction of only one external connector protein between any pair of input proteins analyzed. In this way it was possible to obtain a single network that combines 114 of the 165 proteins modulated by Trop-2 which were subjected to the analysis, with 22 connectors. Statistical significance was verified versus networks generated over the entire reference interactome and versus networks with random composition. For the analysis using the Ingenuity Pathways Analysis software, protein expression values, expressed as ratios between the normalized mean signal intensities between Trop-2 and control transfectants, were converted to fold-change values, where the negative inverse (−1/x) was taken for values between 0 and 1. As the data-set was filtered, no threshold cut-offs were imposed. All the molecules (Swiss-Prot identifiers) were mapped onto the Ingenuity Knowledge Base as focus points. The Ingenuity Knowledge Base organises protein interactions into an ontology format, as extracted by manual curation from published experimental results. Networks of focus molecules were generated by maximising specific connectivities, i.e. actual interconnectedness between molecules versus that with all molecules in the Knowledge Base. Networks were ranked by scores (negative log of the p-value calculated by right-tailed Fisher's exact test) that takes into account the number of eligible molecules in the network and its final size as well as the input data-set size and the total number of molecules in the Ingenuity Knowledge Base included in networks. The higher the score, the lower the chance of stochastic interaction networks. Focus molecules were then mapped onto the Ingenuity Canonical Pathways.

[0094] Statistical Analysis

[0095] The Two-way ANOVA test was used to compare the tumor growth curves (Rossi, Di Lena et al. 2008).

REFERENCES

[0096] Alberti, S. (1999). “HIKE, a candidate protein binding site for PH domains, is a major regulatory region of Gbeta proteins.” Proteins 35: 360-363. [0097] Alberti, S., S. Miotti, et al. (1992). “Biochemical characterization of Trop-2, a cell surface molecule expressed by human carcinomas: formal proof that the monoclonal antibodies T16 and MOv-16 recognize Trop-2.” Hybridoma 11: 539-5. [0098] Alberti, S., M. Nutini, et al. (1994). “DNA methylation prevents the amplification of TROP1, a tumor associated cell surface antigen gene.” Proc. Natl. Acad. Sci. USA 91: 5833-7. [0099] Balzar, M., I. H. Briaire-de Bruijn, et al. (2001). “Epidermal growth factor-like repeats mediate lateral and reciprocal interactions of Ep-CAM molecules in homophilic adhesions.” Mol. Cell. Biol. 21(7): 2570-80. [0100] Barreiro, O., M. Zamai, et al. (2008). “Endothelial adhesion receptors are recruited to adherent leukocytes by inclusion in preformed tetraspanin nanoplatforms.” J Cell Biol 183(3): 527-42. [0101] Basu, A., D. M. Goldenberg, et al. (1995). “The epithelial/carcinoma antigen EGP-1, recognized by monoclonal antibody RS7-3G11, is phosphorylated on serine 303.” Int. J. Cancer 62: 472-479. [0102] Brown, W. J. and M. G. Farquhar (1989). “Immunoperoxidase methods for the localization of antigens in cultured cells and tissue sections by electron microscopy.” Methods Cell Biol 31: 553-69. [0103] Brummelkamp, T. R., R. Bernards, et al. (2002). “A System for Stable Expression of Short Interfering RNAs in Mammalian Cells.” Science 296(5567): 550-553. [0104] Chalk, A. M., C. Wahlestedt, et al. (2004). “Improved and automated prediction of effective siRNA.” Biochem Biophys Res Commun 319(1): 264-74. [0105] Chong, J. M. and D. W. Speicher (2001). “Determination of Disulfide Bond Assignments and N-Glycosylation Sites of the Human Gastrointestinal Carcinoma Antigen GA733-2 (C017-1A, EGP, KS1-4, KSA, and Ep-CAM).” J. Biol. Chem. 276(8): 5804-5813. [0106] Ciccarelli, F., A. Acciarito, et al. (2000). “Large and diverse numbers of human diseases with HIKE mutations.” Hum. Mol. Genet. 9: 1001-7. [0107] Cubas, R., S. Zhang, et al. (2010). “Trop2 expression contributes to tumor pathogenesis by activating the ERK MAPK pathway.” Mol Cancer 9(1): 253. [0108] El Sewedy, T., M. Fornaro, et al. (1998). “Cloning of the murine Trop2 gene: conservation of a PIP2-binding sequence in the cytoplasmic domain of Trop-2.” Int J Cancer 75(2): 324-30. [0109] Elbashir, S. M., J. Harborth, et al. (2001). “Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells.” Nature 411(6836): 494-8. [0110] Fornaro, M., R. Dell'Arciprete, et al. (1995). “Cloning of the gene encoding TROP-2, a cell-surface glycoprotein expressed by human carcinomas.” Int. J. Cancer 62: 610-8. [0111] Freeley, M., J. Park, et al. (2007). “Loss of PTEN expression does not contribute to PDK-1 activity and PKC activation-loop phosphorylation in Jurkat leukaemic T cells.” Cell Signal 19(12): 2444-57. [0112] Giulietti, A., L. Overbergh, et al. (2001). “An overview of real-time quantitative PCR: applications to quantify cytokine gene expression.” Methods 25(4): 386-401. [0113] Goldstein, A. S., T. Stoyanova, et al. (2010). “Primitive origins of prostate cancer: In vivo evidence for prostate-regenerating cells and prostate cancer-initiating cells.” Mol Oncol. [0114] Guerra, E., M. Trerotola, et al. (2013). “The Trop-2 signalling network in cancer growth.” Oncogene doi: 10.1038/onc.2012.151. [Epub ahead of print]. [0115] Guerra, E., M. Trerotola, et al. (2008). “A bi-cistronic CYCLIN D1-TROP2 mRNA chimera demonstrates a novel oncogenic mechanism in human cancer.” Cancer Res 68(19): 8113-8121. [0116] Hakomori, S. I. (2002). “Inaugural Article: The glycosynapse.” Proc Natl Acad Sci USA 99(1): 225-32. [0117] Hemler, M. E. (2003). “Tetraspanin proteins mediate cellular penetration, invasion, and fusion events and define a novel type of membrane microdomain.” Annu Rev Cell Dev Biol 19: 397-422. [0118] Jacinto, E., V. Facchinetti, et al. (2006). “SIN1/MIP1 maintains rictor-mTOR complex integrity and regulates Akt phosphorylation and substrate specificity.” Cell 127(1): 125-37. [0119] Klein, C. E., B. Hartmann, et al. (1990). “Expression of 38-kD cell-surface glycoprotein in transformed human keratinocyte cell lines, basal cell carcinomas, and epithelial germs.” J. Invest. Dermatol. 95: 74-82. [0120] Koul, D., R. Shen, et al. (2005). “Targeting integrin-linked kinase inhibits Akt signaling pathways and decreases tumor progression of human glioblastoma.” Mol Cancer Ther 4(11): 1681-8. [0121] Le Naour, F., M. Andre, et al. (2006). “Membrane microdomains and proteomics: lessons from tetraspanin microdomains and comparison with lipid rafts.” Proteomics 6(24): 6447-54. [0122] Levy, S. and T. Shoham (2005). “The tetraspanin web modulates immune-signalling complexes.” Nat Rev Immunol 5(2): 136-48. [0123] Linnenbach, A. J., B. A. Seng, et al. (1993). “Retroposition in a family of carcinoma-associated antigen genes.” Mol. Cell. Biol. 13: 1507-1515. [0124] Livak, K. J. and T. D. Schmittgen (2001). “Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.” Methods 25(4): 402-8. [0125] Minguez, P., S. Gotz, et al. (2009). “SNOW, a web-based tool for the statistical analysis of protein-protein interaction networks.” Nucleic Acids Res 37(Web Server issue): W109-14. [0126] Naquet, P., H. Lepesant, et al. (1989). “Establishment and characterization of mouse thymic epithelial cell lines.” Thymus 13(3-4): 217-26. [0127] Parekh, D. B., W. Ziegler, et al. (2000). “Multiple pathways control protein kinase C phosphorylation.” EMBO J 19(4): 496-503. [0128] Polishchuk, R. S., E. V. Polishchuk, et al. (2000). “Correlative light-electron microscopy reveals the saccular-tabular ultrastructure of carriers operating between the Golgi apparatus and the plasma membrane.” J. Cell Biol. 148: 45-58. [0129] Rosse, C., M. Linch, et al. (2010). “PKC and the control of localized signal dynamics.” Nat Rev Mol Cell Biol 11(2): 103-12. [0130] Rossi, C., A. Di Lena, et al. (2008). “Intestinal tumor chemoprevention with the antioxidant lipoic acid stimulates the growth of breast cancer.” Eur J Cancer 44: 2696-2704. [0131] Sarbassov, D. D., D. A. Guertin, et al. (2005). “Phosphorylation and regulation of Akt/PKB by the rictor-mTOR complex.” Science 307(5712): 1098-101. [0132] Semizarov, D., L. Frost, et al. (2003). “Specificity of short interfering RNA determined through gene expression signatures.” Proc Natl Acad Sci USA 100(11): 6347-52. [0133] Trerotola, M., P. Cantanelli, et al. (2013). “Up-regulation of Trop-2 quantitatively stimulates human cancer growth.” Oncogene 32 222-233. [0134] Trerotola, M., S. Rathore, et al. (2010). “CD133, Trop-2 and alpha2beta1 integrin surface receptors as markers of putative human prostate cancer stem cells.” Am J Transl Res 2(2): 135-44. [0135] Wang, J., R. Day, et al. (2008). “Identification of Trop-2 as an oncogene and an attractive therapeutic target in colon cancers.” Mol Cancer Ther 7(2): 280-5. [0136] Wen, H. C., W. C. Huang, et al. (2003). “Negative regulation of phosphatidylinositol 3-kinase and Akt signalling pathway by PKC.” Cell Signal 15(1): 37-45. [0137] Zhang, X. A., A. L. Bontrager, et al. (2001). “Transmembrane-4 superfamily proteins associate with activated protein kinase C (PKC) and link PKC to specific beta(1) integrins.” J Biol Chem 276(27): 25005-13.