AT507402A1 - METHOD FOR TESTING THE IRRITING OR ALLERGENIC POTENTIAL OF A PRODUCT - Google Patents

Description

The present invention relates to a method for identifying irritating and / or allergenic substances.

In the last few years, the development of in vitro tests as alternatives to animal experiments for toxicological objects has become increasingly important. One aspect is the identification of low molecular weight chemicals capable of inducing allergic contact dermatitis.

Antigen presenting cells of the skin play a major role in inducing contact sensitization and are therefore potential candidates for the establishment of in vitro systems. Langerhans cells have been proposed to be used in such systems (Tuschl, H., and Kovac, R., 2001. Toxicol, In Vitro 15, 327-331), but since these cells are difficult to isolate in sufficient numbers, For example, dendritic cells (DCs) derived from peripheral blood monocytes (PBNC-DCs) or from CD34 + stem cells (CD34-DCs) may also be used. Early work focused primarily on the analysis of DC maturation markers or on expression changes of immune-relevant genes, e.g. Cytokines and chemokines.

Dietz et al. (2000 Biochem Biophys Res. Commun 275, 731-73 8) analyzed changes in transcription during the maturation process of PBMC-derived immature DCs (iDCs) using a cDNA microarray containing probes for 4110 known genes. 291 genes were found to be upregulated while 78 genes were downregulated. A similar study was conducted by Chen and colleagues (2000 Biochem Biophys Res. Commun 290, 66-72) with mouse DCs treated with lipopolysaccharide (LPS) to effect maturation. A microarray containing probes for 514 genes showed the differential expression of 72 genes. In 2001, La Naour compared gene expression in iDCs and DCs matured by TNF (Le Naour et al., 2001. J. Biol. Chem. 276, 17920-17931). Several groups used Affymetrix arrays to compare various inflammatory stimuli and LPS for their ability to induce DC maturation (Lindstedt et al., 2002 Int Immunol 14, 1203-1213). Moschella and colleagues analyzed changes in the expression of 408 immune genes during DC maturation induced by TNF, CD40L, IFN-γ or IL-7 (Moschella et al., 2001 Br. J. Haematol. 114, 444-457).

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In an earlier work, an immunospecific DNA microarray was established, and it has been shown that exposure of iDCs to the contact sensitizers NiS04 and Bandrowski base (BB) resulted in upregulation of several genes following treatment of iDCs was not induced with the stimulant SDS (Szameit et al., 2008 Clin. Chem. 54: 525-33).

It is an object of the present invention to provide a method to identify irritating and / or allergenic substances, and to distinguish between irritating / allergenic and non-irritating / non-allergenic substances.

The present invention relates to a method for identifying the irritating or allergenic potential of a product comprising the steps of: a) contacting the product with immature dendritic cells, b) determining the amount of gene products of the genes PHLDB3, FAB-P4, ABCG2, FBN2, SP0CD1 and SLAMF1 expressed in said cells upon contact with the product, c) subtracting the amount of gene products and the genes PHLD-B3, FABP4, ABCG2, FBN2, SPOCD1 and SLAMF1 expressed in said cells without contact with the product, from the b) certain quantities to obtain a set of product-induced quantities of gene products for each of said genes; d) comparing the product-caused quantities of gene products obtained under c) for each of said genes with an assay of product caused quantities of gene products for each of said genes, said assay arrangement of product-induced amounts of gene products f r, each of the said genes of at least two allergenic products and at least two irritating products and optionally provided of at least two products, which are neither allergenic, are still irritating; and wherein the comparing is performed by a pattern recognition method that recognizes an allergenic pattern and an irritating pattern, and optionally a non-allergenic and non-irritating pattern; and e) identifying an allergenic potential of a. Pro

when the comparison under d) results in a pattern, and identification of an irritating potential of a product if the comparison under d) results in recognition of an irritating pattern, and optionally identifying a non-allergenic and non-irritating product, if the comparison is under d) results in the recognition of a non-allergenic and non-irritating pattern.

It has surprisingly been found that the set of six genes (PHLDB3, FABP4, ABCG2, FBN2, SP0CD1 and SLAMF1) is sufficient to fully correlate the product to an allergenic or irritating potential (or the product as allergenic or irritating To identify potential).

In the first step of the present method, a product which is unknown in terms of its irritating / allergenic potential is contacted with immature dendritic cells. Upon contact with the product, the response of the dendritic cells to the product in step b) is observed relative to the expression of the group of the six genes mentioned above. These expression profiles are then normalized, relative to each of these genes, for non-irritating and non-allergenic substances in step c). This can be done in a variety of ways. If a microarray is used for determination of expression levels and RNA is the gene product to be determined, the RNA can preferably be labeled fluorescently (for example by two fluorescent dyes) and from a normal (ie non-allergenic and non-irritating)

Value (for example, a value only for the solvent of the product) are subtracted. Also, absolute levels of expression can be determined and subtracted from measured (or known) normal values. The gene products (expression products) to be determined are preferably RNA, but may also be proteins.

For example, in a preferred embodiment, the raw data are generated by measuring the amount of fluorescently labeled nucleic acid sequences generated based on the genes expressed in the immature dendritic cells ("foreground intensity values"). This signal is then indicated by the corresponding "background value". subtracts (for example, the values derived from a nonspecific signal (for example, the nonspecific signal on a microarray (which, for example, by nonspecific binding or autofluorescence

NACHGEF.E1CHT ···································································· •··································································································································· if two fluorescent dyes are used, subtraction from the " background " preferably carried out independently for both fluorescent dyes)). The foreground intensities of the product are then subtracted from measured or known numbers for the expression patterns without contact with the product from the respective amounts determined under step b) to give a set of product-induced amounts of gene products for each of the mentioned To get genes. Preferably, these values are derived experimentally, for example from an experiment where the immature dendritic cells are contacted only with the solvent of the product (ie without the product); this embodiment has the additional advantage that effects of solvents are also visible and can be subtracted and excluded).

The data can then be normalized, for example, by first using Loess Normalization and then Scale, but all other normalization methods can also be used. In the method according to the present invention, the sequence of normalization / subtraction is not critical. For example, in the case of fluorescence analysis, subtractions of controls (for example the dendritic cells, treated only with solvent (especially log2 (first color) -log2 (second color)) may usually be performed after normalization.

In step d) the expression patterns, related to the group of six genes, are compared by pattern recognition methods. These methods are readily available to those skilled in the art. A preferred method for pattern recognition is the use of feature selection and incorporation of the construction of a classifier. In the examples, a Nearest Shrunken Centroid method was used as implemented in the pamr software, available at www.bioconductor.org. This identified a range of classifiers from 4500 genes down to six genes, each achieving 100% prediction accuracy. Such methods are readily available in the prior art, for example in (WO-2008/037806 A, Tibshirani et al. (PNAS 99 (10) (2002), 6567-6572 and Stat. Science 18 (1) (2003), 104-117) and Hastie et al. ("The Elements of Statistical Learning", Springer, 2001, especially pages 9-39, 79-111, 182-

POSSIBLE • · ········································································································ ···························································································································································· The method according to the present invention may include further pattern recognition techniques such as "k-Nea-rest-neighbor (KNN)". "Support Vector Machines (SVM)", "Linear Discriminant Analysis" (LDA) ", "Artificial Neural Networks (ANN) " and others. The rule for classification of an unknown sample is usually derived from a distance measurement of the unknown sample to a representation of one of the two classes, that is the "Centroid", the "Nearest Neighbor". or any other representation of the classes. Alternatively, regression or model-based approaches that compute a least-squares least-squares decision limit or maximum similarity estimate will be applicable in the method of the present invention.

With the method according to the present invention, the identification of an allergenic or irritating substance in a product (and optionally the absence of allergenic or irritating properties) can be identified with 100% accuracy. This is also shown in the example section.

The assay arrangement may contain more than the at least two expression data from each group of compounds. Preferably, the assay arrangement comprises the product-induced amounts of gene products of (independently) at least 4, preferably at least 6, more preferably at least 10, especially at least 20 substances of each class (allergen, irritating, non-allergenic and non-irritating). The larger the audit order data, the more robust and less refined pattern matching can be applied.

The group of six genes is necessary (and sufficient) to allow for 100% accuracy of the method, however, additional allergen / irritant markers may be included in the method of the present invention. Preferably, these markers can be selected from the following Table A (which also includes the group of six, as mentioned above, including the GeneBank entry numbers for these genes).

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Table A: GeneBank entry number in parentheses MS4A3 (NM 006138) PDLIM4 (NM 003687) PHLDB3 (NM_198850) MARCKS (NM_002356) LOC124220 (NM_145252) FBN2 (NM_001999) S100A10 (NM_002966) BAU (NM_001702) SLAMF1 (NM_003037) AOAH (NM_001637) EPSTII (NM_033255) ABCG2 (NM004827) SPOCD1 (NM_144569) LOC541471 (AK001796) ITGAD (NM_005353) RELB (NM_006509) DHRS9 (NM_0 05771) CENTD3 (NM_022481) IL4I1 (NM_172374) GPIBA (NM_000173) S100A4 (NM_002961) EHF (NM_012153) BTN2A2 (NM_181531) LY75 (NM__00234 9) PPFIBP1 (NM_003622) H2AFY2 (NMJ318649) CYBRD1 (NM_024843) MBOAT2 (NM_138799) BU678941 (THC2680668) EMP2 (NM_001424) AK026517 (THC2637222) TNFRSF12A (NM_016639) FABP4 (NM_001442) SLC9A9 (NM_173653) CD38 ( NM_001775) SYT11 (NM_152280) ARHGAP22 (NM_021226) BTN2A2 (NM_181531) PLA2G4C (NM_003706) POLE4 (NM_019896) SYT11 (NM_152280) IL1RN (NM_173842) LGP2 (NM_024119)

Immature dendritic cells undergo maturation upon contact with allergenic substances. This effect is used in the method of the present invention to identify irritating and allergenic substances in products tested with this system. When immature dendritic cells are contacted with an allergenic substance, among other things, the cell begins to upregulate the transcription of various genes. Although other substances that show no allergenic properties, but show irritating properties, also a non - specific general stress response in

SUBSEQUENT

These dendritic cells, accompanied by upregulation and downregulation of various genes, do not result in the specific gene expression pattern of the genes of Table A. *** " Therefore, the genes identified in Table A enable unambiguous identification and discrimination between irritating / allergenic substances from non-irritating / non-allergenic substances.

In a preferred embodiment of the present invention, the amount of gene products of at least one, of at least two, of at least three, of at least four, of at least 10, of at least 15 normalizing genes is also determined. The expression rate of a normalizing gene in a dendritic cell is approximately identical upon contact with an irritating / allergenic substance (that is, the amount determined varies only about ± 10%) with the amount expressed in dendritic cells that are non-irritating / allergenic Substances are contacted. The normalization gene (s) can be selected from the group disclosed in Table B.

FOLLOW-UP • «• * • V • · - 8 • • • • • • • • * • • • • • • • • • • • • • • • • • • • • • Table 1: Normalizing genes Gen - Einoanos Gene Input Gen Input Gen Input San Input 3rd Symbol Number Symbol Number Symbol AASDHPPT NUJ15423 CHP NMJD07238 FU30092 AB014S14 MZF NMJ15517 PU89 NMJ91307 TERT ADAM33 NUJ28220 CIAMN1 NM .020313 FU38379 AK066698 MLLTB NM.ooea »PUS7 NMJ19042 TFCP2 ADJPOR2 NM.0240S1 OP28 NM.033082 FNTA NMJQ2Q27 MRP63 ΝΗ.02« αβ 0RICH1 NK.017730 TfPT ADPGK NMJ31264 CLA8P1 NM.015282 FPGS NMJ049S? MRPL15 NMJ14175 RABIS NMrt030981 TGFBRAP1 ΑΚΛΡ10 NMJ07202 CLDN11 NMJ009602 FO0P3 NM.003934 MRPL20 NMJM7W1 RAB28 NMJ04249 THAP7 AKAP13 MIL0M738 CtPX NMJ906660 FZR1 NM_Oie2S3 MRPL28 NMJ06428 RA83GAP2 NMJ12414 TH0C7 ALG9 NMJ24740 CN0P2 NMJS1BZ35 0A8RG2 NMJ9B904 MRPL34 NMJ23937 RAB5B NMJ02868 THUMP02 ALPP12 NMJ31313 CNFN NMJD32488 SCSI NMJ06302 MRPL37 MMJ16491 RAC1 NMJ96629 IMCOf ANKRD49 NMJ17704 cnoti NMJH6284 (3FM1 NMJ24996 MRPL36 NMJ32478 RAD17 NM.002673 TMEM1 ATC NMJ00Q36 CNOT2 NMJH4315 5L.U02 NMJ12064 MRPL4 NMJ15966 RAF1 M4J0Q28M TMEM103 APLN NMJ017413 CN0T3 NMJD14518 BLYGTK NMJ4S262 MRPL43 NMJ32112 RAP8N NMJ32645 TMEM11 Aprin NM_0lS032 CN0T8 NM_01S455 GMPS NM.003875 MRPS10 NMJ16141 RARA NMJQ0964 TMEM14C AQP2 NMJ00496 CN0T7 NMJQ64028 0NPDA2 NMJ38335 MRPB15 NMJ312B0 RA8BF3 TMEM34 AK129920 AQR NM.014691 CNP NMJ033153 GNPTO NMJ32S20 URPB16 NM016066 R & BP4 NM_006610 TMa "ARCNt NMJ016S5 COOl IMJH87H GNRK2 NM.001501 URP822 NMJ20191 RBM17 NMJ32905 TMEM58 ARFGE Fl NMJOOG421 COI27A1 NM_032888 QON4L NMJ01037533 MT1A NMJ05949 RBM26 NMJ22116 TMEM85 ARID2 NMJ62641 corei NMJ01B451 GPBP1L1 NMJ21639 MT3 NMJ05954 RBM3 NM.001017430 TMUB1 ARIH1 AJD09771 COPC NM_007263 GPD1 NMJ05278 MTOH NMJ78812 RBMX2 NMJ16Q24 TNXB ARNT MM_OO1088 COP86 NMJ9B189 GP1AP1 NMJ05698 MTHFR NMJ05057 RBX1 Nht.014246 TRIM10 ARS2 NMJ62600 00X15 NM_076470 GPKOW NMJ15998 MTX1 NMJ98883 RER1 NM_007033 TRIM4 ARBO NM001M9 OOX8A NMJXMC74 GTF3C1 NMJ01S20 MUC3A M55405 RFWD2 NMJ22457 T8PAN1 AS0B NMJ24095 CF1X2 NMJ006650 GYLTL1B NMJ52312 MUCO AK096772 MC8A NMJ21932 TSPAN14 ASXL1 l * L015338 CPNE6 NM_006032 H6PO NMJ04265 MYAOM NM.13B373 RLTPR AX090421 TTF1 ATG4A NMJ78271 CPSF2 NM017437 HARB NMJ021O9 MYC M13930 RMNP5B AK094065 U8A52 ÄTP5C1 NMJ05174 CPSF4 NM_008693 HQAC8 NMJ18486 MYH14 NMJ24729 RNF148 NMJ30963 UBE2D2 ATP5C NMJ006478 CR594735 CR594736 HEA8 NMJ06631 MYOG NMJ02479 RNF34 NMJ94271 UBE2F ATP6V0E NMJ0394S CREB3L1 NM_052854 HERC4 NM_00I017972 NACA NMJ06594 RNF38 N M.194328 UBE2G2 BC12L12 NMJ38639 CRHR1 M4JD04382 HIF0P5 NMJ15700 NAGLU NMJ00263 RN PSI NM_006711 UBE2I 8HLHB5 NM_1524I4 CROCC NMJ14675 HMGN1 NMJ0496S NATO NMJ15654 RP11-53SK18.3 AL632120 UBE3A BM56I346 ΒΜ56134Θ CRSP3 NMJD04830 HMQX2 NMJ02134 NCBP2 NMJ07362 RPI1-56A21.1 NM.0010057S1 UCK1 BTF3 NM_001207 CSPP1 NM.024790 HNRPC NMJ313I4 NCOR1 NM_0063l 1 RP6-186C19.1 NM_173571 UGT2B10 BTN2A3 NMJ24018 CSTF2 HNRPK NM_001325 NM_002140 NDNL2 NMJ38704 RPL14 NM.003973 UMOO Cl0ort27 NMJ52710 CTCF NM.006565 HNRPR NMJ05828 NDUFA11 NMJ7S614 RPL15 NMn002948 UN01887 C10wf32 NMJ44591 CTRB2 NMJ0102S200 WASLS5 NMJ54108 NDUFA4 NMJ02489 RPL18A NMJ00960 UQCRC2 C10orf4 NM.203433 CXCL5 NM_002994 HSAJ2425 AJ002425 NDUFB7 NM.004146 RPL19 NM_000981 UOCRH C11orf10 NMJ14206 CYB56101 NMJ82560 HSPBP1 NMJ12267 NEK & NMJ78170 RPL21 ΝΜ.0009Θ2 U6P16 C11orf42 NMJ 73525 CAB1 NM.Q210B0 H8PC142 NMJ14173 NFKBIL2 NMJ13432 RPL35 NMJ072Q9 USP4 C11orf54 NMJ14039 DBF4B NMJ45663 HSPC148 NMJ16403 NFX1 NMJ02504 RPL36 NMJ15414 ÜSP4B C11arf56 NMJ32127 DCAKD NMJ24819 HTATIP NMJ06388 NHN1 NM.144604 RPL36AL NM_001001 UTP14A C12off11 NMJ1B164 0CTN4 NMJ16221 HTR3A NMJ13621 NHP2L1 NMJ05008 RPP14 NM "007042 UTP15 C14orf10 NMJ17917 DOT NM.001355 ICOSLG NMJ15259 NKX2-5 NMJ04387 RPS15 NM.001018 UTPia Cl4orf111 NMJ16962 00X1 $ NMJ06773 IK NM_0060 $ 3 NME2 NM_002512 NM_001009 RP35 VARSL C14orf12l NMJ38380 00X49 NMJ19070 IL27 NM_145659 N0C4L NMJ24078 RPUS01 NM.0S8192 VCY C14WI2 NMJ04894 00X50 NM_024045 ILF2 NMJXM515 N0L1 NMJ06170 RPUS04 NM 032795 VPS29 C14orM3 NMJ 94278 DE NR ΝΜ.003Θ77 INTS12 NMJ20395 N0L5A NM_006392 RTBDN NM.031429 VPS4A C150H20 NMJ25049 DHRSX NMJ45177 IQSEC2 NMJ15075 Notum NM_178493 C15orf44 SAPS1 NMJ14931 Vps54 NMJ30800 DHX16 NM.003587 ISG20L2 NM. 030980 NRN1 NMJ16588 SCARA5 NMJ738 33 VPS72 C16orf3 NMJ01214 DHX30 NM.138614 KCNK7 NMJ33347 NUBP1 NM.002484 SCNN10 NMJ02976 VWA1 C16orf35 NM_001039476 < 11222513.2 NR.002164 K0ELR1 NMJO60O1 NUP68 NMJ02532 SCRN3 NMJ24583 WBSCR18 Cieorf57 NMJ24598 DKFZP434AQ131 NMJ18991 KIAA0133 NMJ14777 NUP11 NMJ14089 SOF2 NMJ06923 WOR3 C1flWf7B NMJ52339 OKFZP5 & 6P0123 AL080220 KIAA0409 NMJ 15324 NYX NMJ22587 SOHD NM.003002 WOR53 C17orf42 NMJ24883 OM WO NMJ04943 K1AAOS53 NM_001002909 OGDH NMJ02541 SFC11L1 NMJ14300 WOR73 C17 "®5 NMJ78642 DNAJA3 NM ^ .005147 KIAA0892 NMJ15329 OGFR NM" 007345 SEMA4B NMJ20210 WOR74 C1flwf19 NMJ 82577 DNAJB12 NM_001002762 KIAA0913 CR610954 OGT NM. 181672 S6PT2 NM.001008491 WOR74 C19od24 NMJ17914 0NAJC1 NMJ22365 KIAA1160 NMJ20701 OR10H2 NMJ13939 SERINC3 NMu006611 WFDC10B C190ff42 NMJ24104 DNAJC19 NM.145261 KIAA1967 NMJ21174 0R2H1 NM.030863 SETMAR NMJ06515 WFDC3 ClOfllOP NMJ17850 DNAJC8 CR619944 NM_020738 K1D1NS220 OR4D2 NMJ01004707 SF1 NMJ04630 WHSC1L1 C1orf117 NMJ82623 0ÖLPP1 NM_02043 8 KTN NMJ12311 ORMDL3 NMJ39280 SF3A1 NMJ05877 W1RE C1wf161 NMJ17953 0PF2 NM.006266 KLC2 NMJ22822 OTOF NMJ04248 & F3B1 NMJ12433 wtz C1od188 NMJ73795 DPH1 NMJ01383 KLF11 NM.003597 OXSM NMJ17897 8FRS14 NMJ142B4 XAB1 C1örf2 NM_006589 DPT NM.001937 XLK14 ΝΜ "02204β OXT NMJ00915 SFTPC NM ^ 003016 YIPF5 csoorme NM.023936 D6CR1L2 NMJ13441 KLK9 NMJ12315 PAC81 NMJ18026 BH3BP2 NM ^ 003,023 YTHOF2 C20orf14l NM 080739 DUS3L NMJ20175 KLP1 NMJ20378 PAIP2 NMJ18480 Sin3A NM.015477 YWHAB C20wM4 NM.018244 DUSP11 NM.003564 KRAS NMJ33360 PAN3 NMJ75854 SKI NM.003036 ZBE04 C20ortS2 ΝΜ.0Θ0746 DYRK18 NM.004714 KRT61 NMJ02281 PANK4 NMJ16218 SKIP NM.130766 ZBTB16 C2torf70 NM.058100 E2F3 NM.001949 KRTAP1-3 IM_030966 PAP01 NMJ16109 SLC25A3 NM_213612 C22orf27 ZC3H14 NMJ 53044 NM_001050 E2F4 NM_021046 KRTAP5-8 PAXIP1 NM.007349 SLC25A36 AL049246 ZCCHC4 C22orf »NM.014306 E4F1 NM.004424 KRTAP5-9 NMJ05563 PCID1 NMJ06360 8LC20A2 NMJ01532 ZCSU C2or12S NM_015702 E8AG9 NM.004215 Ku * -UEV NMJ99203 PCLKC NMJ17675 SLC35B3 NMJ1S946 ZOHHC3 C2FT (f33 NM.020104 EDG5 NMJ04230 SituationLocated 3 NMJ06014 PCNP NMJ2D3S7 3LC5A2 NMJ03041 ZDHHC6 C4orf6 NM-003704 EEF1D NMJ32378 L0B1 NM.003893 PEMT BC007S72 SLC6A8 NM00S629 ZFP91 C5orf14 NMJ024715 EFNB3 NMm00140B LEMD2 NMJ 81336 PHF8 NMJ15107 SLC9A3R2 NM.00478 "ZFYVE19 C5orf22 NM_018356 E1F282 NMJ14239 LEREP04 NMJ18471 PHPT1 NMJ14172 Slit3 AL122074 ZNF146 COorflSS NM_033112 EIF2B4 NMJ72195 LFNG NMJ01040168 PLA2Q4D BC034S71 SMAD9 NMJ0590S ZNF212 C6orf72 NMJ38785 EIF3S7 NMJ007S3 LGR6 NM_001017403 PLCB2 BC009009 SMCR5 AF467442 AF269596 ZNF271 C9orf73 ELAVL1 NM_001419 IHB NMJ00894 PMPCB NMJ04279 SNRPA NM.004596 ZNF302 C9orfl63 M4_152571 ENTP02 NMJ01246 LM06 NM..006150 PMS2CL BC041364 SNRPB2 NM_003092 ZNF320 C9cmT74 NM_030914 EPN3 NMJ17957 LONPt NMJ31490 POLL NMJ13274 SNX6 NMJ21249 ZNF324

Single analog NMJ96253 mjton & NMJ13342 NMJ04257 NMJ30573 NMJ26076 NMJ25264 NMJ19026 NM.0Q3274 NMJ01031703 ΝΜ_003β70 NMJMS2 NMJU241 NMJ14264 NM_ 198149 NMJ10454 NMJ31434 NM.01 * f0 & NMJ06776 NNL03301? NMJ06727 NMJ3092? NMJ07344 NM.QQ3333 NMJB1638 NMJ80678 NM.iaase »NMJ942S9 NM.iaoead NMJ31432 NMJ01075 NMJ03361 NMJ39015 nm_om» ö M36847 NMJ06447 NM_003383

NMJ3223Q NM_006649 NMJ32175 nmjisooi NM 020 442 NM 004679 NMJ57180 NMJ13245 NMJ16516 NMJ0S997 NMJ22834 NMJW317 NMJ06784 NMJ82627 NMJ32858 NMJ16093 NMJ18093 NMJ72008 NMJ60614 NMJ17776 NMJ33264 AK131404 NMJQ7266 NM.030799 NMJI6258 NMJ03404 NMJI4B38 NMJ06008 ΝΜ_207ββΟ ΑΥ629351 NMJ61706

NMJI659B ΝΚ.013373 NMJ53023 NMJ32850 NMJQ7145 NM0122S6 NMJ0G629 NMJ16443 NMJ07333 NMJ14347 ·· ♦ · ♦ · · · · · · · · · · · · · · · ····· - 9 - C9orf97 NM_139248 ERAL1 NM 005702 LRP10 NM.01404S POLR2F NM_021974 SON NNM38927 ZNF384 NMJ33476 CACNA1C NM.000719 EXOSC10 NM_001001998 LRRC42 NM.052940 POLR2J NM.008234 SPAST NMJ014946 2NF407 A8051490 CAMTA1 AY037153 FAM113A NM.Q22760 LRRC47 NM_020710 POLR2J2 NM 032959 SPINK7 ΝΜ_03256β ZNF434 NM017810 CASP8AP2 NMH01211S FAM119B NM_208914 LRRC57 NM.153260 POT1 NM 015 450 NM 005987 SPRR1A ZNF444 NM_018337 NM_201453 CBW03 FAM12QAOS NM_198641 LSM3 NM.014463 PPAP2C NM.177543 SPRR2B NM_001017418 ZNF468 NM.001008401 CCDC43 NM.144609 FAM29A NM_017645 LTBP3 NM.021070 PP1AL4 NMJ78230 SS18L2 NMJ01630S ZNF511 NM.148808 CCDC44 NM.016380 FAM35A NM019054 LZTS2 NM.032429 PP1G NM 004792 SSTR3 NM_001051 ZNF525 AK098804 CCDC56 NM_001040431 FAM44A NMJ48894 M7 4509 M74S09 PPYR1 NM 005972 ST6GALNAC4 NM_175039 ZNF526 NM_002991 CCL24 NMJ33444 FAM8SA NM.024519 MAK10 NM_024635 PQBP1 NM 005710 STAMBP NM_213622 ZNF574 NM_037370 NM.Q22752 CCNDBP1 FASTK NM.006712 MAP3K3 NM_203351 ZNF583 NM_152478 PRCC NM.005973 8UM01 NM_001005781 NM_008725 CD6 FAU NM.001997 MAP3K7 NM .003186 PRJC285 NM.033405 TAAR5 NM_003967 ZNF593 NM_138477 NM_01587l COAN1 FBS1 NM.0224S2 M604 NM.003925 PRIMA1 NMJ78013 TAF12 NM_005844 ZNF613 NM.02484O CDC2L1 NM.033489 FBXL19 NM.019O85 MEF2B AK057161 Prosc NMj007198 TAF1B NM_005680 ZNF614 NM.025040 CDC2L5 NMJJ03718 FBX017 AK021860 MEG3 NRJW2766 PRPF31 NMJHS629 TAF2 ΝΜ_0031β4 ZNF646 NMJM4699 COH22 NM.021248 FBX03 NM.033406 MESP1 NM_01B870 PRPSAP2 NM_002767 TAOK2 NMJ316151 ZNF851 NM_145106 C0K3 NM.001258 FGD1 NM.004463 METT11D1 NM_022734 PRR13 NM.00100S354 TAS1R1 NM.138697 ZNF655 NM_001009956 CDKSR2 NM.003936 FGF3 NM .005247 METTL5 NM_014168 PRR3 ΝΜ_0252β3 TBC1D17 NM.024682 ZNRD1 NM_170783 CEACAM19 NM_020219 FKBP2 NM_00447 0 AK027396 MFSD2 PRSS8 NM.002773 TBKBP1 NM.014726 CGGBP1 NM_001006390 NM_031904 FKSG44 MFSD7 NM.032219 PSEN1 NM.000021 TBP NM.003194 CHAC1 FLAD1 NM_024111 NM_025207 MGC13138 NM_033410 PTER NM 001001484 NM_030900 T8RG4 CHCHD5 FU20125 AK096990 NM_017876 MGC23280 NM_144683 NM_006756 PJGJR mjooosco TCEA1 CHFR NM 018223 FLJ20309 NM_017759 MGC33894 NM_152914 PTMS NM.002824 TCERG1 NM_006706 CHGA NM.001275 FU20487 NM_017841 MGC4618 NM_032326 PTPN11 NM 002834 TDP1 NM018319 CHMP8 NM.024591 FU20551 NM_017875 MIER1 NM_020948 PUM1 NM.014676 TEA03 NM.003214

As used herein, the term " gene product " either RNA, in particular mRNA or a peptide, polypeptide or protein resulting from expression (transcription or transcription / translation) of a gene.

Immature dendritic cells to be used in the method of the present invention may be prepared by methods known in the art (see, eg, US-2004/109851, De Smedt et al., 2002 Arch. Dermatol. Res. 294, 109-116).

The immature dendritic cells used in the method of the present invention are preferably immature PBMC-DCs.

According to the preferred embodiment of the present invention, the immature dendritic cells are derived from peripheral blood monocytes (PBMCs) or CD34 + stem cells.

Methods of making and isolating these types of cells are known to those skilled in the art (De Smedt et al., 2002 Arch. Dermatol. Res. 294, 109-116).

According to another preferred embodiment of the present invention, the amount of at least six gene products in step b) is determined.

To increase the accuracy of the method of the present invention, it is preferred to determine in step b) the amount of more than the group of six gene products.

According to a particularly preferred embodiment of the

NACHGERBCHT 1 ·· ** #t ···· # »* • ················································································································································································································· Method comprises step b) the determination of the amount of at least five further, preferably at least 10 further gene products, which are also further evaluated in steps c) to e), wherein the further gene products are selected from the genes MARCKS, LOC124220, FBN2, S100A10 , BAU, AOAH, EPSTIII, LOC541471, ITGAD, RELB, DHRS9, CENTD3, IL4I1, GP1BA, S100A4, EHF, BTN2A2, LY75, PPFIBPl, H2AFY2, CY-BRD1, MBOAT2, BU678941, EMP2, AK026517, TNFRSF12A, SLC9A9, CD38 , SYT11, ARHGAP22, BTN2A2, PLA2G4C, POLE4, SYT11, IL1RN, LGP2, MS4A3 and PDLIM4.

Particularly preferred is a method according to the present invention, wherein in step b) the amount of gene products of the genes PHLDB3, MARCKS, LOC124220, FBN2, S100A10, BAU, SLAMF1, AOAH, EPSTII, ABCG2, LOC541471, ITGAD, RELB, DHRS9, CENTD3 , IL4I1, GP1BA, S100A4, EHF, BTN2A2, LY75, PPFIBPl, H2AFY2, CY-BRD1, MBOAT2, BU678941, EMP2, AK026517, TNFRSF12A, FABP4 SLC9A9, CD38, SYT11, ARHGAP22, BTN2A2, PLA2G4C, POLE4, SYTII, ILIRN, LGP2, MS4A3 and PDLIM4 is determined, and further evaluated in steps c) to e).

As described above, the gene product to be quantified may be a nucleic acid (ie, RNA) or a proteinaceous (eg, polypeptide) molecule. The method to be used to determine the amount of these molecules depends on the type.

According to a preferred embodiment of the present invention, the amount of at least six gene products is determined by reverse transcribing RNA, in particular mRNA to produce cDNA, and subjecting said cDNA under a real-time polymerase chain reaction (PCR) and / or hybridization assay.

When the amount of RNA is determined, a reverse transcription step is needed to produce cDNA that can be quantified by methods such as real-time PCR or hybridization assays. Of course, it is also possible to combine the step of reverse transcription with a real-time PCR.

The hybridization assay is preferably a microarray assay or a microsphere assay.

Both techniques involve the use of target-specific probes immobilized on a solid support.

In the case of microarrays, the solid support is essentially

FOLLOW-UP ··· ♦ # · Μ ·· ·· · • ♦ · · · · · · · · · · In the case of microspheres, the solid support is essentially spherical. Solid carriers to be used in such methods are known in the art. Particularly preferred surfaces to be used in the microchip according to the present invention are at least partially coated with a phenolic resin polymer having a functionality of from 6 to 15, preferably from 7 to 10, most preferably 8. Such surfaces are described, for example, in WO-03/027675 A, Preininger et al. (Anal Biochem 330 (2004), 29-34).

A microarray (also commonly known as a gene chip, DNA chip, or bio-chip) is a collection of microscopic DNA spots attached to a solid surface such as glass,

Plastic or silicon chip forming an assembly for the purpose of expression profiling which simultaneously monitors levels for a large number of amplified nucleic acids. Microarrays can be fabricated using a variety of technologies, including fine pointed needles on glass slides, photolithography using previously prepared masks, photolithography using dynamic micromirror devices,

Ink-jet printing or electrochemistry on microelectrode arrays.

A microarray comprises a large number of immobilized oligonucleotide molecules, provided in high density on the solid support. A microarray is a highly efficient tool for detecting tens, hundreds or even thousands of different amplified products according to the present invention in a single detection step. Such microarrays are often provided as slides or plates in certain microtiter plates. In the prior art, a microarray is defined both as a miniaturized array of binding sites (ie, a material, the support) and as a support comprising miniaturized binding sites (ie, the array).

According to a preferred embodiment of the present invention, the amount of at least six gene products is determined using antibodies which bind to said gene products.

A further aspect of the present invention relates to a microarray which has on its surface probes for the genes PHLDB3, FABP4, ABCG2, FBN2, SP0CD1 and SLAMFl -immobil _

1 FOLLOW-UP ····························································································································································································································· wherein said microarray comprises at least 10%, preferably at least 20% more preferably, at least 30% of the total number of probes which are probes for the genes PHLDB3, FABP4, ABCG2, FBN2, SPOCD1 and SLAMF1.

Preferably, the microarray according to the present invention immobilizes on its surface probes for genes, said microarray having at least 20%, preferably at least 40%, more preferably at least 60% of the total number of probes, probes for the genes PHLDB3, MARCKS, LOC124220, FBN2, S100A10, BAU, SLAMF1, AOAH, EPSTI1, ABCG2, SPOCD1, LOC541471, ITGAD, RELB, DHRS9, CENTD3, IL4I1, GPIBA, S100A4, EHF, BTN2A2, LY75, PPFIBP1, H2AFY2, CYBRD1, MBOAT2, BU678941, EMP2, AK026517, TNFRSF12A, FABP4, SLC9A9, CD38, SYTII, ARHGAP22, BTN2A2, PLA2G4C, POLE4, SYTII, ILlRN, LGP2, MS4A3 or PDLIM4.

It is further preferred to additionally have probes for normalizing genes on the microarray, for example at least 5, preferably at least 10, more preferably at least 15 normalizing genes selected from Table B.

According to a particularly preferred embodiment of the present invention, the microarray contains probes of 60%, preferably 80% of the genes of Table A, wherein FABP4, PHLDB3, FBN2, SLAMF1, ABCG2 and SPOCD1 are always present on the microarray.

Another aspect of the present invention relates to a kit containing probes for the genes PHLDB3, FABP4, ABCG2, FBN2, SPOCD1 and SLAMF1. Preferably, the kit additionally comprises probes for at least 5, preferably at least 6, in particular all of the genes MARCKS, LOC124220, S100A10, BAU, AOAH, EPSTII, LOC541471, ITGAD, RELB, DHRS9, CENTD3, IL4I1, GPIBA, S100A4, EHF, BTN2A2, LY75, PPFIBPl, H2AFY2, CYBRD1, MBOAT2, BU678941, EMP2, AK026517, TNFRSF12A, SLC9A9, CD38, SYTII, AR-HGAP22, BTN2A2, PLA2G4C, POLE4, SYTII, ILlRN, LGP2, MS4A3 and PDLIM4. It is also preferred if the kit further comprises probes of at least 5, preferably at least 10, more preferably at least 15 normalizing genes selected from Table B. Preferred kits therefore contain probes wherein at least 20%, preferably at least 40%, more preferably at least 60% of all probes are selected from the group consisting of at least 6 genes selected from the group consisting of PHLDB3, MARCKS, LOC124220, FBN2, S100A10, BAU, SLAMF1, AOAH,

POSSIBLE »· ········································ EPISTI1, ABCG2, SPOCD1, LOC541471, ITGAD, RELB, DHRS9, CENTD3, IL4I1, GPIBA, S100A4, EHF, BTN2A2, LY75, PPFIBP1, H2AFY2, CY -BRD1, MBOAT2, BU678941, EMP2, AK026517, TNFRSF12A, FABP4, SLC9A9, CD38, SYTII, ARHGAP22, BTN2A2, PLA2G4C, POLE4, SYT11, IL1RN, LGP2, MS4A3 and PDLIM4 and at least 5, preferably at least 10, more preferably at least 15 normalizing Genes selected from Table B. The probes to be used according to the present invention are nucleic acid molecules derived from said genes having the same or complementary nucleic acid sequence. Preferred probes are the following:

Gene name systematic name sequence EPSTIl NM_033255 NM_173842 TL1RN GPlBA NM_000173 FHLDB3 NM 198850 ARHGAP22 NM_021226 POLE4 NM_019896 AK026517 AK026517 TNFRSF12A NM_016639 SYT11 NM_152280 NM_002966 S100A10 NM 001424 EMP2 CENTD3 BTN2A2 RELB H2AFY2 S100A4 SLC9A9 NM022481 NM181531 NM_006509 NM_018649 NM_002961 NM 173653

AGAAGAGAAGCATTTAGAGAGCATCAGCAATACAAAACCGCTGAGTTCTTGAGCAAACTG

TATTCCTGCATTTGTGAAATGATGGTGAAAGTAAGTGGTAGCTTTTCCCTTCTTTTTCTT

TTTCTAGTTTTCTTATCAGGATGTGAGCACTCGTTGTGTCTGGATGTTACAAATATGGGT

GAGGAAGATTGCAGGGGCGGGAAGAAACTATTTATTGGTGCTCCTGTGATACCGAATTAA

ATCAGATGCTGCTCCAACCATGCAGTTCCTGGTGAGGGTCAGAAGGGGACGGTACCAAGA

CTGTGGATGAATTTGCTTTTCTGGAAGGTACTTTAGATTGATTGCCGAGCGGGGCAGTTT agcaatagatctggtagttgtgtgggcagatacttactgtatgaatgaaagaacat

TCACTCAGATGTCCTGAAATTCCACCACGGGGGTCACCCTGGGGGGTTAGGGACCTATTT

GCTCTTCTGCTATGAAGTAGTAAAAGGCAGTCTATAATTAACTGACAGACCTAACTGAAG

AGAAAAGTTAAATACCAGATAAGCTTTTGATTTTTGTATTGTTTGCATCCCCTTGCCCTC

TTCCGGAGCTGGGTTGCTTCTGCTGCAGTACAGAATCCACATTCAGATAACCATTTTGTA

ATATTTGATACGTACGGGTTCCATGAGAGATTTTGGGTTTTAAAGGAATC-GTTTTACTGC

GTTATTGAGGACTTTAAAGAGCTTTTGTTTATTTGGGTTAATATTTATGACATTTGACAT

CAGACTTGAAGGTGGGGGGTAGGTTGGTTGTTCAGAGTCTTCCCAATAAAGATGAGTTTT

AAATCCTTTCAAAATTCTTAAATCTTCTGTTCCTCCTTTTTCCAAGGGAAGAGGGCAAAA

ATAAGCAGCCCAGGAAGAAATGAAAACTCCTCTGATGTGGTTGGGGGGTCTGCCAGCTGG

TTTTTTGCTTTCCAAACAGAATCTCTGGGGCACAAGTTTTACACTCAAGCTAAGTATAAC

POSSIBLE 99 · Ι Μ ···· ····················································· ······ · 99 99 99 99 99 9 - 14 -

LY75 NM_002349 NM_005771 tgtggttatcactttaagttttgacacctagattatagtcttagtaatagcatccactgg DHRS9 ACTCATTTAGATCGTGCTTATTTGGATTGCAAAAGGGAGTCCCACCATCSCTGGTGGTAT FABP4 NM_0 01442 CTCACCTTGAAGAATAATCCTAGAAAACTCACAAAATGTGTGATGCTTTTGTAGGTACCT SP0CD1 AK097227 TGGAGGTGGCTGATAAGAGTÄGAGTTTCAAAATCTCTTTAAACCTTCCTAAAGCAATGAT MS4A3 NM006138 taatatccagtcattaaggagttgtcactcttcatcagagtcaccggacctatgcaatta BAU NM 001702 CGGCCGGCCTGGCACCGTTTTTTAAACACCCCCATCCCTCGGGAAGCAGCCAGCTCCCCA

LOC541471 ΑΚ001796 GCAAGACGTATGCAGTTTTCATTGACATCTTTTGGAGAAACTGACAAACTGGACTTGACT

ΕΆΒΡ4 NM_001442 NM_004827 AAGGGACGTTGACCTGGÄCTGAAGTTCGCATTGAACTCTACAACATTCTGTGGGGATATA ABCG2 CTGGGGCTTGTGGAAGAATCACGTGGCCTTGGCTTGTATGArrGTTATTTTCCTCACAAT LGP2 NM024119 CATACTGTACTCAGAATCACGACATTCCTTCCCTACCAAGGCCACTTCTATTTTTTGAGG AOAH NM 001637 TTTACAAACTTCAATCTTTTCTACATGGATTTTGCCTTCCATGAAArCATACAGGAGTGG PPFIBP1 NM_003622 GGAGTAATGTGCCGATTCTGAAGTTGCCACAAAAAATAAGACACTGGTGAATGÄGAGTäT IL1RN NM_173843 NM_002356 AAGATTTTATTGTAAAACAGAGCTGAAGTCACAGGAAGTAGGGAACTTTGCACCCAACAT MARCKS GGTAAGGTCATGAACCACTATTTTTGATCCATTATTCCAATTAAGAATGCGTGTCAAAAC FBN2 NM 001999 GTTCCCTTGAAAGGGAACACCTGGCATTCTGTGGTGTTTCGTGCTGTCTTAAATAATGGT

LOCI2422Ο NM 145252 CCäCCAGTTAATCTCACATACTCAGCAAACTCACCCGTGGGTCGCTAGGGTGGGGTATGG SPOCD1 NM 144569 TGTTTGAACTTCCTGTTTGACAÄTGTTTGCTGTTGATTTTTTGTTCAATAAAGAATTTGG PDLIM4 NM_0 03 6 8 7 TGCTCCCACGCCTGCTTCTTAAGGTCCCTGCTCGGCCGGTGTAAATATGTTTCACCCTGT ITGAD NM005353 GCTAAGCACCTTCTCGGAGAGATAGAGATTGTAATGTTTTTACATATCTGTCCATCTTTT CYBRD1 NM 02 4843 CCCTCATTTTTTGGATAGTCACCAGACCGCAATGGAAACGTCCTAAGGAGCCAAATTCTA MBOAT2 NM138799 TTGTTCCTAAATGGTATTTTCAAGTGTAATATTGTGAGAACGCTACTGCAGTAGTTGATG POLE 4 NM019896 tcagaggagagacttggataatgcaatagaagctgtggatgaatttgcttttctggaagg SYT11 NM 152280 GCTGACTTTGGCTTTCACATTTGTTCTTTCCAGAGCTAACTGATAAGAGTGGAGGAGGAA PLA2G4C NM_003706 tccagatggccagaatgaatgtgatagttcagaccaatgccttccactgctcctttatga BU678941 BU678941 agcgaccatccagtcatttatttccctccattcccaatgatgtacacacgactaagaagg EHF NM_012153 tatctgtttactgtctcatctgaactgatcccaggtgaacggtttattgcctagatttgt SLAMF1 nm_003037 tctgtgcctcagtttctctctcaggataaagagtgaatagaggccgaagggtgaatttct CD38 NM_0017 7 5 tgaaaaatcctgaggattcatcttgcacatc tgagatctgagccagtcgctgtggttgtt IL4I1 NM_17237 4 ccagttatctctccaaaacacgacccacacgaggacctcgcattaaagtattttcggaaa BTN2A2 NM_181531 cctggtcgagcagggcagtactggaccaggtctacgtcagcattcaggttcaatggggac SLAMF1 NM 003037 aggcgcagaacagagcgttacttgataacagcgttccatctttgtgttgtagcagatgaa

The kit of the present invention contains probes which can be used to detect the presence of those gene products of immature dendritic cells which are expressed when said cells are contacted with irritating and / or allergenic substances. I REPLACED | ·········· + · · · · · · · · · # · · · · · · · · · · · · · · · · · ······································

The present invention is further illustrated by, but not limited to, the following figures and examples.

Figure 1 shows dose-response experiments after 24-hour exposure to iDCs with increasing concentrations of chemicals. CD86 expression compared to the solvent control was determined by the method of Overton (1988) (solid line). PI staining was performed to determine cytotoxicity and viability is expressed as 100% cytotoxicity [%] (dotted line). Means and SD of at least three independent experiments are shown. Dashed vertical lines mark the concentrations chosen for all further exposures. Analysis of iDCs exposed to NiS04, BB, and SDS have been previously presented (Szameit et al., 2008).

Fig. 2: The red line in Fig. 2 shows the misclassification error of an eightfold cross-validation as a function of the threshold (the number of genes used for pattern recognition). A range of classifiers from 4500 genes down to 6 genes has been identified, each of which achieves 100% prediction accuracy. Three arbitrary sets of sentences were taken from the record: a 6-gene set, a 48-gene set, and a 4500-gene set. The distinctiveness of these genes was then assessed again in a 8facen cross validation approach. This procedure (random selection of sets and 8-fold cross-validation) was then repeated 100 times and the particular cross-validation error is shown below in the box plots. The high error rates show that arbitrarily selected geneticists are largely unusable in distinguishing between allergenic and irritating substances.

Figure 3 shows the multiple changes (M-values) of the six genes necessary for the classifier (PHLDB3, FABP4, ABCG2, FBN2, SP0CD1 and SLAMF1) as measured in the single microarray experiments (chemically treated with Solvent-treated DCs). Fails changes derived from experiments using an allergenic chemical are shown in red, expression values derived from experiments using an irritating chemical are shown in green. Differences in gene expression between experiments with single-handedness ····· ♦ ···· ♦ · · · · · ·············································································· · · · · · · · · · · · · · · 16 Allergenic chemicals and tests using irritating chemicals are clearly visible.

Fig. 3 shows EXAMPLE:

Materials and procedures:

Culture of iDCs and chemical exposure of iDCs were generated as previously described (De Smedt et al., 2002. Arch. Dermatol. Res. 294, 109-116). Briefly: 400 U / ml IL4 and 1000 U / ml GMCSF (Strathman Biotech) were added to the incubation medium. The medium was refreshed every other day.

On day six, iDCs were treated with various concentrations of the following chemicals and solvent controls for 24 hours:

Allergens: Bandrowski base N, N '' - (2,5-diamino-2,5-cyclohexa-diene-1,4-diylidene) bis (1,4-benzenediamine)), BB (ICN Biomedicals Inc); NiSO4 (Merck); 2,4-dinitrobenzenesulfonate, DNBS; 2,4-dini-trochlorobenzene, DNCB; Eugenol (4-allyl-2-methoxyphenol), Eug; a-hexylcinnamaldehyde, CA; Hydroquinone, HQ (all Sigma-Aldrich).

Irritating substances: sodium dodecyl sulfate, SDS (Merck); TritonX-100, Tri; Methyl salicylate, MS (both Sigma-Aldrich). DNBS, NiSO 4, SDS and Tri were dissolved in water, BB, DNCB, Eug, CA, HQ and MS in 0.1% DMSO (Merck).

Controls were performed only with the solvents (that is, without the allergenic / irritating substance) to evaluate solvent effects.

DCs derived from 3-4 human donors were used for each chemical.

Flow cytometric analysis

Flow cytometric analyzes were performed as previously described (Szameit et al., 2008). The following antibodies were used: FITC anti-human CDla, PE anti-human CD14, PE anti-human CD86 (BD Pharmingen): measurements were taken on a Coulter Epics XL-MCL (Beckman Coulter Inc.) with EXP032 ™ ADC XL 3 Color vl.IC - Expo32 vl.2 Analysis vl.IC (Beckman Coulter Inc.). DCs were defined by light scattering, dead cells were collected out, and fluorescence histograms were scored by the method of Overton (Overton, 1988, Cytometry 9, 619-626).

Propidium iodide (PI) staining was performed to reduce cytotoxicity.

t «······································································································································································································································. φ φ φ ·· ·· ·· φφ ΦΦ φ - 17 - toxicity (Sigma-Aldrich). Cells were harvested and 500 μΐ of culture were incubated with 10 μΐ PI (0.2 mg / ml in PBS) for 5 min at 4 ° C. The percentage of PI positive cells was measured by flow cytometry and viability was reported as "100% cytotoxicity [%]". expressed. RNA extraction DCs were harvested by centrifugation (10 min, 300 g, 4 ° C) and cells were resuspended in Trizol (Invitrogen). Total RNA was isolated using trizole as described in the manufacturer's protocol. RNA pellets were resuspended in 100 μM RNase-free water and 350 μM buffer RLT (Qiagen) and 250 μM EtOH were added. Samples were applied to RNeasy microcolumns (Qiagen) and RNA purification was performed according to the manufacturer's protocol. On-column DNase treatment was performed using the supplied RNase-free DNase. RNA was eluted with 2 x 14 μM RNase-free water. RNA amplification, labeling and hybridization immune toxicity chip

Template Switching PCR (TS-PCR) Amplification of 50 ng of total RNA was described previously (Petalidis et al., 2003 Nucleic Acids Res. 31, el42; Lauss et al., 2007 Virchows Arch. 451, 1019-1029 ) using Power Script RT Kit and Advantage 2 PCR Kit (Clontech). All resulting first-strand cDNA (10 μΐ) was used as template for the second-strand amplification reaction. PCR was performed with the following settings: 95 ° C for 1 min, 17 cycles for 95 ° C for 10 sec, 65 ° C for 10 sec, 68 ° C for 6 min. The cycle number for the PCR was adjusted. to obtain cDNA derived from the exponential phase of the PCR. PCR products were purified using the QIAquick PCR purification kit with Buffer PB (Qiagen) according to the manufacturer's protocol and labeled with Klenow polymerase exo-minus Epicenter 10000U (Biozym). 3 μg PCR product was mixed with 3 μΐ (N) i0 primer (OD = 125) to a final conversion volume of 94.5 μΐ. The reaction was incubated at 98 ° C for 5 min. And cooled on ice for 5 min. Next, the following reagents were added: 12 μL of Klenow buffer, 10 μM of a dNTP mixture containing 0.23 mM dA / dT / dGTP and 0.07 mM dCTP, 2 μM Cy3 or Cy5 dCTP (GE Healthcare ) and 1.5 μΐ Klenow polymerase. The implementation was

POSSIBLE »· ······································································································································································································································ C incubated for 2 hours and terminated at 95 ° C for 3 min. After labeling, cDNAs derived from chemically treated DCs and solvent treated DCs were combined and microconcleaning was performed using Microcon YM30 columns (Millipore Corporation).

After blocking the chip surface as previously described (Szameit et al., 2008), cDNAs were co-hybridized at 42 ° C overnight on a microarray using 20 μM DigEasy hybridization buffer (Roche Diagnostics).

Gesamtgen-Arrav RNA samples derived from DCs exposed to NiSO 4, BB, DNBS, DSD, or Tri were additionally analyzed with 44k human whole genome 0.01 microarrays (Agilent Technologies). RNA expression levels of chemically treated DCs and DCs exposed to solvent control were analyzed on a microarray using the Two-Color Low RNA Input Linear Amplification Kit PLUS (Agilent Technologies) according to the manufacturer's protocol. For each amplification, 200 ng total RNA was used and amplified samples were prepared for hybridization using the Gene Expression Hybridization Kit (Agilent Technologies). Hybridization was performed overnight at 65 ° C in a rotary hybridization oven (Agilent Technologies).

Structure of the Immunotoxicity Chip 66 immune-related genes, 7 housekeeping genes, 8 negative controls and external and internal normalization controls were run on ARChip Epoxy glass slides (Austrian Research Centers GmbH - ARC, Seibersdorf, Austria) using an Om-nigrid Arrayer (GeneMachines ) spotted. Probe design and external normalization controls (Lucidea Universal Score Card System, GE Healthcare) have been previously described in detail (Szameit et al., 2008). In addition to external normalization controls, probes for internal normalization were included in the chip design, allowing for normalization without the need to add extra RNA. Therefore, the risk of inaccurate normalization due to pipetting errors is reduced. Similar to Yang et al. (Yang et al., 2002 Nucleic Acids Res. 30, el5) was a series of 10 non-differentially expressed human RNA pool (Stratagene) pools of human RNA.

POSSIBLE Μ ···························· ·· Φ # · · φ Φ «· ·· ·· ·· ΦΦ ΦΦ φ - 19 -. The RNA was reverse transcribed using TS-PCR amplification as described earlier in this paper. The resulting cDNA was spotted onto the immuno-toxicity chip in serial dilutions (1: 3) beginning at 96 ng / μΐ. Since expression of most genes is not affected by exposure of DCs to chemicals, the signal intensities of the fluorescent dyes Cy3 and Cy5 on these probes should be the same in a two-color microarray experiment.

data analysis

Hybridizations performed on the immunotoxicity chip were scanned using a GenePix 4000A scanner (Molecular Devices) with adjusted settings (equal for both wavelengths) avoiding saturated signals. Raw image data was extracted using GenePix 3.0 software (Molecular Devices).

Hybridizations performed on whole genome arrays were scanned using an Agilent DNA microarray scanner and raw imaging data was extracted using the Agilent Feature Extraction Software (v9.5.3.1). The software package Limma for the R computer environment was used for data analysis by both systems (Smyth and Speed, 2003, Methods 31, 265-273). Limma is part of the Bioconductor project at www.-bioconductor.org (Gentleman et al., 2004 Genome Biol. 5, R80). For each hybridization, background intensities of foreground intensities for each spot were subtracted. Data derived from the immune toxicity chip was normalized using internal normalization controls using Loess normalization. For global genome experiments, global loess normalization was performed.

To identify the most promising candidate genes for the identification of sensitizers, experiments performed on RNA derived from allergen-exposed DCs were combined, a linear model was adapted, and the Bayes empirical method (Smyth, 2004, Stat. Appl. Genet Mol. Biol. 3, Article 3) was used. The significance of the differentially expressed genes were classified by the B statistic (Smyth, 2004). In addition, gene expression changes in DCs treated with each chemical were analyzed separately. For the immunotoxicity chip, in-array replicates have been incorporated into the

POSSIBLE ·· • ft ···· • ft • · · · · · · · · · · · · ft • ft. · · · Ft · · · · · ···· • · - 20 -

Analysis integrated as previously described (Smyth et al., 2005 Bioinformatics 21, 2067-2075). If a gene was represented by more than one probe or several identical probes on the whole genome array, only the compartment induction and the B value of the highest B probe were taken. Technical replicates (dye swaps) and biological replicates (experiments using DCs from different blood donors) were specified for each chemical. For whole genome arrays, only biological replicates were performed. For probe selection, classification, and cross-validation of total genome data, a nearest-shrink-centroid method (implemented in the pamr software available from www.-bioconductor.org) was chosen (Tibshirani et al., 2002 Proc. Natl. Acad USA 99, 6567-6572). It has been chosen for several reasons: it has been extensively used in the literature, it enables multi-class classification, and it carries out feature selection, classification, and cross-validation in one go.

In short, it calculates several different possible classifiers using different shrinkage limits (that is, different numbers of genes) and finds the best cross-validation threshold. Here, the classifier with the smallest number of genes was selected (largest threshold) if more than one threshold gave the same cross-validation results. The same procedure was applied to the two-class problem of predicting allergen versus irritants and to the five-class problem of predicting the 5 different chemicals used in the tests.

In order to visualize differences in gene expression between DCs exposed to various chemicals, hierarchical clustering of genes significantly expressed after treatment of iDCs with one of the chemicals (B> 1) was performed.

Real-time PCR

Quantitative real-time PCR was performed as previously described (Szameit et al., 2008) using TaqMan gene expression assays (Applied Biosystems) with RNA isolated from 4 DC cultures treated with SDS or DNBS and the appropriate solvent controls for 24 Std. Performed (Table 1).

POSSIBLE REVIEW I • ···············

Table 1: Genes analyzed with quantitative real-time PCR. Genes were randomly selected from genes identified as differentially expressed with the whole genome array after exposure of iDCs to sensitizers. Taq-Man gene expression tests were used (Test ID).

Gene Symbol Receiving Number Test ID ATF3 NM_001030287.2; NM_004024.4 NM_001040619.1; NM_001674.2; Hs00231069_ml B2M NM_004 04 8.2 Hs99999907_ml CLCF1 NM_013246.2 Hs00757942_ml CXCL2 NM_00208 9.3 Hs00236966 ml FREQ NM_014286.2 Hs00179522_ml IL8 NM_000584.2 Hs00174103_ml RIPK2 NM_003821.5 Hs00169419_ml RPLPO NM_053275.3; NM 001002.3 Hs99999902_ml SOD2 NM_001024 4 65.1; NM_001024466.1; NM_000636.2 Hs00167309_ml STK17A NM_0047 60.2 Hs00270504 ml

The same RNA used for the microarray experiments was used. Triplicate copies of each sample were made, normalized to 2 housekeeping genes (RPLPO, B2M) and biological replicates were analyzed using the 2Δ ^ method (Livak and Schmittgen, 2001, Methods 25, 402-408). After log2 transformation of the resulting multiple inductions, a sample t-test was performed to analyze whether fold inductions were significantly different from 0 (p <0.05).

Results

Flow cytometry analysis and dose-response experiments

Prior to exposure, cells were analyzed for expression of monocyte / macrophage marker CD14 and DC marker CDla using flow cytometry. All cultures were consistently CD14 negative and approximately 90% of the cells were highly CDla positive (data not shown). Effects of increasing concentrations of HQ, CA, DNBS, DNCB, Eug, MS and Tri on expression of the maturation marker CD86 and PI inclusion were analyzed. Concentrations giving 10% - 20% cytotoxicity I REPLACED 1 - 22 -

were selected for all chemicals (240 pg / ml DNBS, 2 pg / ml DNCB, 212 μg / ml CA, 320 μg / ml Eug, 25 μg / ml HQ, 100 μg / ml MS and 7.5 μg / ml Tri) (Fig. 1). Cytotoxic concentrations (> 20% cytotoxicity) could result in nonspecific upregulations of CD86 expression (Szameit et al., 2008) and were therefore not used. Previous studies have already presented dose-response curves for iDCs treated with various concentrations of NiSO 4, BB and SDS (Szameit et al., 2008). In these studies, gene expression in iDCs exposed at concentrations giving <10% cytotoxicity was analyzed. In order to obtain 10% to 20% cytotoxicity in the present work, the doses of BB and SDS were increased to 10 μg / ml and 90 μg / ml, respectively.

Analysis of PI staining in DCs exposed to increasing concentrations of the chemicals showed a reduction in viability for NiSO4, CA, DNBS, DNCB, Eug, HQ, and SDS. No concentration dependence was detected for the analyzed concentration ranges of BB, MS and Tri. While higher concentrations of tri were analyzed in previous experiments and resulted in a rapid reduction in viability, higher concentrations of BB and MS could not be analyzed because of limits of solubility. Except for DNCB and HQ, treatment with increasing chemical concentrations resulted in increased CD86 expression. For DNCB and HQ, the amount of CD86 ++ cells after exposure to DCs was reduced to concentrations> 2 μg / ml (viability 87 +/- 2% or 25 μg / ml (viability 81 +/- 7%, (Figure 1)). ,

Immune toxicity chip

All experiments using RNA derived from iDCs exposed to allergens (NiSO 4, BB, DNBS, DNCB, HQ, CA or Eug) were combined and a linear model was adapted. Log-fold inductions and B-values of the genes that were significantly up- or down-regulated were calculated and rated by the B-statistic. Thirty-six probes were found which represent a panel of markers that could be useful in distinguishing sensitisers and irritating substances. The probe for TNFRSF1A is nonspecific (Szameit et al., 2008). Therefore, this gene was excluded from the analysis.

To analyze the applicability of the marker panel, the number of differentially expressed genes after exposure was determined

DETERMINED by iDCs among individual chemicals as a percentage of the number of genes of the marker panel (Table 2). Up to 26.7% of the markers were found to be upregulated with irritating agents even after iDC exposure and <14.3% were down-regulated. The weak or moderate allergens (HQ, CA, Eug) were positive for> 33.3% of the upregulated markers and> 19.1% of the downregulated markers. The stronger allergens (NiSO 4, BB, DNBS, DNCB) clearly separate from the irritating substances with> 46.7% upregulated and> 57.1% downregulated genes.

Table 2: Number of differentially expressed genes after exposure of iDCs to individual chemicals as a percentage of the number of marker panel genes.

All Sensitizers NiS04 BB DNBS DNCB HQ CA Eug SDS MS Tri up-regulated 100 93.3 60 46.7 66.7 40 33.3 60 26.7 6.7 20 down-graded 100 76.2 71.4 66, 7 57.1 33.3 38.1 19.1 14.3 0 14.3

Whole genome Arrag

In addition to analysis with the immunotoxicity chip, changes in gene expression in cells treated with allergen (NiSO 4, BB, DNBS) or irritating (SDS, Tri) were analyzed as compared to solvent-treated cells to find genes are not represented on the chip of the invention, which could be suitable as marker genes.

Out of> 44,000 probes on the whole genome array, 1741 genes were found to be upregulated upon exposure of iDCs to allergens, but not to irritating substances. In addition, 2007 genes were identified as down-regulated.

To assess the predicted value of these genes for the determination of allergenic potential, feature selection, classification and cross validation were performed. Only 6 genes were necessary to predict allergenic potential with 100% accuracy in cross validation (Table 3, Figures 2 and 3).

A similar classifier has been designed to predict the different chemicals used. 64 genes were necessary to predict the 5 different chemicals with 100% accuracy in cross-validation (Table 3).

Table 3: Genes necessary to predict the allergenic potential of chemicals or to predict various chemicals as determined by cross-validation. flannwmft_Eingang · never

Genes necessary to anticipate all potential NM_198850 NM_0014 4 2 NM_004 827 NM_001999 NM_14 4 569 NM 003037 PHLDB3 (ENST00000292140) FABP4 (W60781) ABCG2 FBN2 SP0CD1 SLAMF1

Genes which are necessary for various chemicals to predict HS3ST1 NM_005114 EDNRB NM_003991 EPSTI1 NM_033255 KITLG NM_000899 CDK5RAP2 NM_01824 9 G0S2 NM_015714 TPM1 NM_000366 TAL1 NM_00318 9 DPYSL3 NM_001387 CG018 NM_052818 THC2269852 THC2269852 GBP1 NM_002053 C17orf 60 (ENST00000332935) NM_001085423 RGS2 NM_002923 ENC1 NM_003633 DPYSL3 NM_001387 TPM1 NM 001018004

NACHGEtElC '-) T • ·· · »0 0 0 0 0 • · ·« · · · · «« * · · * · · ·· ····· 25: Gennaine input snuinmar MCEMP1 NM_174 918 SPR NM0Q3124 DKFZP686A01247 NM_014 988 S0D2 BDKRB2 NM_000636 NM_000623 NM_004101 F2RL2 SNX5 BC002724 RAB15 NM198686 RCNL LIPH NM_002901 NM_139248 GBP1 NM_002053 IL15 NM172174 SNN NM_0034 98 CF.S1 NM_001266 KIAA1274 NM_014431 CR601322 CR601322 NM_003122 SPINK1 STAG 3 NM_012447 NM_000756 CRH TPM1 NM_001018004 IFIT3 GR EMI NM__013372 NM_00154 9 AF116678 AF116678 S67044 CD36 EBI3 NM005755 LEPREL1 NM_018192 RGS1 NM_002922 PKIB NM_181795 NDRG2 NM 201535 ÄBCC2 NM_000392 SLAMF7 NM_0 21181 TPM1 NM_001018004 PROC NM 000312 CD36 NM_001001547 METTL7A NM_014033 KLF10 NM 005655 LOC222171 NM_175887 AF131834 AF131834 PMP22 NM_000304

NACHGEnZC; IT

Qanwam ·

GDF15 NM 004864

SNN NM 003498 SIGLEC10 NM 033130 HSD3B1 NM 000862 DUSP1 NM 004417 PDK4 NM 002612 ENC1 NM 003633 ENST00000367932 ENST00000367932

Feature selection, classification and cross validation were performed using a nearest-shrunken centroid method (Tibshirani et al., 2002). The classifier with the lowest number of genes (highest threshold) was chosen if more than one threshold gave the same cross-validation results. The procedure was used to predict the allergenic potential of the chemicals as opposed to the irritating potential, and to predict the 5 different chemicals used in the test. ENST00000292140, W60781 and ENST00000332935 (in parentheses) could be further specified by a BLAST search with the intended sequences.

Hierarchical clustering of the genes, which were significantly up-regulated or down-regulated after exposure of iDCs to one of the chemicals, showed the two main groups. The stimulants (SDS, Tri) clustered in a group, while the sensitizers (NiS04, BB, DNBS) clenched separately. In addition, the 2 main clusters are further divided into 5 smaller sub-clusters, which represent the 5 different chemicals.

Real time t - PCR

Expression of 8 genes found to be upregulated in DNBS-treated DCs with the whole genome array was additionally analyzed by real-time PCR using RNA from DNBS and SDS-treated DCs. Upregulation of expression after DNBS treatment could be confirmed for all genes (p <0.05). Changes in the expression of IL8 and CXCL2 were additionally measured with the immuno-toxicity chip, showing a lower but non-ambiguous upregulation compared to the whole genome and PCR results. Really-

.. .. · 27 * * * * 27 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ... showed a slight but significant up-regulation of ATF3, CLCFl, FREQ and STK17A. No significant induction of gene expression was found for CXCL2, IL8, R1PK2 and SOD2, either with microarrays or with PCR.

discussion

To identify a panel of marker genes with the immunotoxicity chip, a linear model was adapted to the combined experiments using RNA derived from allergen-treated DCs. 36 probes showed significant up- or down-regulation and could therefore be valuable markers for the identification of sensitizers. Then, the work results of linear models were considered, which were adapted for each chemical to find out how much more genes are still being differentially expressed from the marker panel when weak sensitizers are analyzed compared to irritating substances. The results (Table 2) indicate that identification of strong allergens (NIS04, BB, DNBS, DNCB) is possible using the existing assay. For these chemicals,> 46.7% of the genes were up-regulated and downregulated> 57.1% compared to <26.7% and <19.1% for the irritating substances, respectively. However, for weak or moderate allergens (HQ, CA, Eug), the lowest percentage of upregulated genes was 33.3% and 19.1% for the downregulated genes. Therefore, discrimination of irritating substances and weak sensitizers with the current marker panel is difficult, but a larger set of marker genes might facilitate the analysis.

It has been shown in this example that the expression of many immune-relevant genes changes during DC maturation and migration, and that expression of these genes is also altered by exposure of iDCs to allergenic chemicals. Furthermore, other genes that have not been related to the maturation process of DCs to date may also be valuable marker genes. Therefore, gene expression was analyzed in DCs treated with selected sensitizers (NiS04, BB, DNBS) and irritating substances (SDS, Tri) using an overall genome array. The results (1741 genes upregulated, downregulated genes in 2007) indicate that additional relevant marker genes are found Vönnpn p ^ - - I filed later ··· ν ·· ···· ·· t • ··· »· ·· ············································································································································································································································ allows the identification of weak sensitizers. To visualize the relevance of these genes as markers, a hierarchical cluster analysis of all genes that were significantly differentially expressed after exposure of iDCs to one of the chemicals was performed. Furthermore, using these genes, smaller clusters can be found for each chemical, again indicating their relevance.

Finally, in addition to merely identifying differentially expressed genes, it was also evaluated whether a combination of these genes could be used to predict the allergenic potential of chemicals. For both prediction problems, the classification accuracies in cross validation were 100%. This accuracy was achieved with 6 genes for predicting allergens against irritating substances and 64 genes for predicting the 5 chemicals. In further studies, these classifiers must be validated with a large external record to preclude over-adaptation. However, the high prediction accuracy and the low number of genes in the classifiers are very encouraging. While quantitative real-time PCR verified the up-regulation of selected genes after DNBS treatment of iDCs, expression analysis of SDS-treated DCs showed significant upregulation for ATF3, CLCF1, FREQ, and STK17A. For ATF3, FREQ, and STK17A, log-fold inactivations of the microarray results also indicate changes in gene expression, but these results are not significant (B <0). Since real-time PCR has been shown to be more sensitive than microarray analysis, mild expression induction of these genes by SDS is likely. However, compared to PCR results with RNA derived from DNBS-treated cells, induction is weak and still allows differentiation of sensitizers and irritating substances.

Log-fold inductions of IL8 and CXCL2, detected with the immunotoxicity chip, were lower than those detected with the whole genome array or with PCR. This indicates that further optimization of the hybridization protocol may even enhance gene expression detection with the immunotoxicity chip for some probes. Up-regulation of expression of additional genes found to be differentially expressed in this study using the immune toxicity chip

REPLACED - 29 - - 29 -

(CCR7, CXCR4, IL12B, p40, IL15) has already been confirmed by real-time PCR with RNA derived from NiS04 exposed cells in a previous work (Szameit et al., 2008).

FOLLOW-UP ····· * * # # # # # # 110 &gt; 1/9 SEQUENCE LISTING Austrian Research Centers GmbH - ARC &lt; 120 &gt; Method for testing the irritating or allergenic potential of a product <130> R 52677 &lt; 140 &gt; &Lt; 141 &gt; AT A 1442/2008 2008-09-16 &lt; 160 &gt; 48 &lt; 170 &gt; Patent version 3.5 &lt; 210 &gt; &Lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 1 60 DNA Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 1 agaagagaag catttagaga gcatcagcaa tacaaaaccg ctgagttctt gagcaaactg 60 &lt; 210 &gt; 2 &lt; 211 &gt; &lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 2 tattcctgca tttgtgaaat gatggtgaaa gtaagtggta gcttttccct tctttttctt 60 &lt; 210 &gt; 3 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 3 tttctagttt tcttatcagg atgtgagcac tcgttgtgtc tggatgttac aaatatgggt 60 &lt; 210 &gt; 4 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 4 gaggaagatt gcaggggcgg gaagaaacta tttattggtg ctcctgtgat accgaattaa 60 &lt; 210 &gt; 5 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial sequence &lt; 220 &gt;

POST-REPRODUCED ··································································································································································································································· Sample &lt; 400 &gt; 5 atcagatgct gctccaacca tgcagttcct ggtgagggtc agaaggggac ggtaccaaga 60

&Lt; 210 &gt; 6 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 6 ctgtggatga atttgctttt ctggaaggta ctttagattg attgccgagc ggggcagttt 60 &lt; 210 &gt; 7

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 7 agcaatagat ctcggtagtt acgtattggg cagatactta ctgtatgaat gaaagaacat 60

&Lt; 210 &gt; 8 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 8 tcactcagat gtcctgaaat tccaccacgg gggtcaccct ggggggttag ggacctattt 60 &lt; 210 &gt; 9

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Arti fi ci al sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 9 gctcttctgc tatgaagtag taaaaggcag tctataatta actgacagac ctaactgaag 60

&Lt; 210 &gt; 10 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 10 agaaaagtta aataccagat aagcttttga tttttgtatt gtttgcatcc ccttgccctc 60

&Lt; 210 &gt; 11 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence

FOLLOWED 3/9 &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 11 ttccggagct gggttgcttc tgctgcagta cagaatccac attcagataa ccattttgta 60

&Lt; 210 &gt; 12 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 12 atatttgata cgtaggggtt ccatgagaga ttttgggttt taaaggaatg gttttactgc 60 &lt; 210 &gt; 13

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 13 gttattgagg actttaaaga gcttttgttt atttgggtta atatttatga catttgacat 60

&Lt; 210 &gt; 14 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 14 cagacttgaa ggtggggggtaggttggttg ttcagagtct tcccaataaa gatgagtttt 60 &lt; 210 &gt; 15

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 15 aaatcctttc aaaattctta aatcttctgt tcctcctttt tccaagggaa gagggcaaaa 60

&Lt; 210 &gt; 16 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 16 ataagcagcc caggaagaaa tgaaaactcc tctgatgtgg ttggggggtc tgccagctgg 60 &lt; 210 &gt; 17 &lt; 211 &gt; 60

POSSIBLE 4/9 &lt; 212 &gt; DNA &lt; 213 &gt; Arti fi ci al sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 17 ttttttgctt tccaaacaga atctctgggg cacaagtttt acactcaagc taagtataac 60

&Lt; 210 &gt; 18 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 18 tgtggttatc actttaagtt ttgacaccta gattatagtc ttagtaatag catccactgg 60

&Lt; 210 &gt; 19 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 19 actcatttag atcgtgctta tttggattgc aaaagggagt cccaccatcg ctggtggtat 60

&Lt; 210 &gt; 20 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 20 ctcaccttga agaataatcc tagaaaactc acaaaatgtg tgatgctttt gtaggtacct 60

&Lt; 210 &gt; 21 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 21 tggaggtggc tgataagagt agagtttcaa actctcttta aaccttccta aagcaatgat 60

&Lt; 210 &gt; 22 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 22 taatatccag tcattaagga gttgtcactc ttcatcagag tcaccggacc tatgcaatta 60 CODES; · ·· ··· ♦ ···· ················· · T # φ · · · Φ 5/9 &lt; 210 &gt; 23 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 23 cggccggcct ggcaccgttt tttaaacacc cccatccctc gggaagcagc cagctcccca 60 &lt; 210 &gt; 24 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 24 gcaagacgta tgcagttttc attgacatct tttggagaaa ctgacaaact ggacttgact 60 &lt; 210 &gt; 25 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 25 aagggacgtt gacctggact gaagttcgca ttgaactcta caacattctg tggggatata 60 &lt; 210 &gt; 26 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial Sequence &lt; 220 &gt; &lt; 22 3 &gt; Sample &lt; 400 &gt; 26 ctggggcttg tggaagaatc acgtggcctt ggcttgtatg attgttattt tcctcacaat 60 &lt; 210 &gt; 27 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 27 catactgtac tcagaatcac gacattcctt ccctaccaag gccacttcta ttttttgagg 60 &lt; 210 &gt; 28 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 28 tttacaaact tcaatctttt ctacatggat tttgccttcc atgaaatcat acaggagtgg 60

AFTERMARK iT 6/9 &lt; 210 &gt; 29 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 29 birdseed gccgattctg aagttgccac aaaaaataag acactggtga atgagagtat 60 &lt; 210 &gt; 30

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 30 aagattttat tgtaaaacag agctgaagtc acaggaagta gggaactttg cacccaacat 60 &lt; 210 &gt; 31

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 31 ggtaaggtca tgaaccacta tttttgatcc attattccaa ttaagaatgc gtgtcaaaac 60 &lt; 210 &gt; 32

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; 60 60 &lt; 223 &gt; Sample &lt; 400 &gt; 32 gttcccttga aagggaacac ctggcattct gtggtgtttc gtgctgtctt aaataatggt &lt; 210 &gt; 33

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 33 ccaccagtta atctcacata ctcagcaaac tcacccgtgg gtcgctaggg tggggtatgg &lt; 210 &gt; 34 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; sample

NACHGER:; r 7/9 &lt; 400 &gt; 34 tgtttgaact tcctgtttga caatgtttgc tgttgatttt ttgttcaata aagaatttgg &lt; 210 &gt; 35

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 35 tgctcccacg cctgcttctt aaggtccctg ctcggccggt gtaaatatgt ttcaccctgt &lt; 210 &gt; 36

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 36 gctaagcacc ttctcggaga gatagagatt gtaatgtttt tacatatctg tccatctttt &lt; 210 &gt; 37

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 37 ccctcatttt ttggatagtc accagaccgc aatggaaacg tcctaaggag ccaaattcta &lt; 210 &gt; 38

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 38 ttgttcctaa atggtatttt caagtgtaat attgtgagaa cgctactgca gtagttgatg &lt; 210 &gt; 39

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 39 tcagaggaga gacttggata atgcaataga agctgtggat gaatttgctt ttctggaagg

&Lt; 210 &gt; 40 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence

REPLACED &lt; 220 &gt; ···························································································································································· · · &Lt; 22 3 &gt; 8/9 sample &lt; 400 &gt; 40 gctgactttg gctttcacat ttgttctttc cagagctaac tgataagagt ggaggaggaa 60 &lt; 210 &gt; 41 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 41 tccagatggc cagaatgaat gtgatagttc agaccaatgc cttccactgc tcctttatga 60 &lt; 210 &gt; 42 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 42 agcgaccatc cagtcattta tttccctcca ttcccaatga tgtacacacg actaagaagg 60 &lt; 210 &gt; 43 &lt; 211 &gt; &lt; 212 &gt; &lt; 213 &gt; 60 DNA Artificial sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 43 tatctgttta ctgtctcatc tgaactgatc ccaggtgaac ggtttattgc ctagatttgt 60 &lt; 210 &gt; 44 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 44 tctgtgcctc agtttctctc tcaggataaa gagtgaatag aggccgaagg gtgaatttct 60 &lt; 210 &gt; 45 &lt; 211 &gt; &Lt; 212 &gt; &Lt; 213 &gt; 60 DNA Artificial Sequence &lt; 220 &gt; &lt; 22 3 &gt; Sample &lt; 400 &gt; 45 tgaaaaatcc tgaggattca tcttgcacat ctgagatctg agccagtcgc tgtggttgtt 60

&Lt; 210 &gt; 46 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial sequence

NACHGERZ'C: T 9/9 &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 46 ccagttatct ctccaaaaca cgacccacac gaggacctcg cattaaagta ttttcggaaa 60

&Lt; 210 &gt; 47 &lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 47 cctggtcgag cagggcagta ctggaccagg tctacgtcag cattcaggtt caatggggac 60 &lt; 210 &gt; 48

&Lt; 211 &gt; 60 &lt; 212 &gt; DNA &lt; 213 &gt; Artificial Sequence &lt; 220 &gt; &Lt; 223 &gt; Sample &lt; 400 &gt; 48 aggcgcagaa cagagcgtta cttgataaca gcgttccatc tttgtgttgt agcagatgaa 60

SUBSEQUENT

Claims (15)

30 1. A method for identifying the irritating or allergenic potential of a product comprising the steps of: a) contacting the product with immature dendritic cells, b) determining the amount of gene products of the genes PHLDB3, FAB- P4, ABCG2, FBN2, SP0CD1 and SLAMF1 expressed in said cells upon contact with the product, c) subtracting the amount of gene products of the genes PHLDB3, FABP4, ABCG2, FBN2, SPOCD1 and SLAMF1 expressed in said cells without contact with the product , from the respective quantities determined under b), to obtain a set of product-induced quantities of gene products for each of said genes, d) comparing the product-caused quantities of gene products obtained under c) for each of said genes with an assay arrangement of product-induced amounts of gene products for each of said genes, said assay arrangement of product-induced amounts of gene products f for each of said genes of at least two allergenic products and at least two irritating products and optionally of at least two products which are neither allergenic nor irritating; and wherein the comparing is performed by a pattern recognition method that recognizes an allergenic pattern and an irritating pattern, and optionally a non-allergenic and non-irritating pattern; and e) identifying an allergenic potential of a product if the comparison under d) results in recognition of an allergenic pattern, and identifying an irritating potential of a product if the comparison under d) results in recognition of an irritating pattern and optionally identifying a non-allergenic pattern. allergenic and non-irritating product if the comparison under d) results in the detection of a non-allergenic and non-irritating pattern. 2. Method according to claim 1, characterized in that said immature dendritic cells are immature Langerhans cells. • · · • · · * · · • · ···· Μ · · · · · · · 31 3. Method according to claim 1, characterized in that said immature dendritic cells are derived from peripheral blood monocytes (PBMCs) or from CD34 + stem cells. 4. The method according to any one of claims 1 to 3, characterized in that in step b) the amount of at least five further, preferably determined by at least ten other gene products and further evaluated in steps c) to e), wherein the further gene products selected are from the genes MARCKS, LOC124220, FBN2, S100A10, BAU, AOAH, EPSTI1, LOC541471, ITGAD, RELB, DHRS9, CENTD3, IL4I1, GPIBA, S100A4, EHF, BTN2A2, LY75, PPFIBP1, H2AFY2, CYBRD1, MB0AT2, BU678941, EMP2, AK026517, TN-FRSF12A, SLC9A9, CD38, SYTII, ARHGAP22, BTN2A2, PLA2G4C, POLE4, SYT11, IL1RN, LGP2, MS4A3 and PDLIM4. 5. The method according to any one of claims 1 to 4, characterized in that in step b) the amount of the gene products of the genes PHLDB3, MARCKS, LOC124220, FBN2, S100A10, BAU, SLAMF1, AOAH, EPSTI1, ABCG2, SPOCDl, LOC541471, ITGAD , RELB, DHRS9, CENTD3, IL4I1, GPIBA, S100A4, EHF, BTN2A2, LY75, PPFIBPl, H2AFY2, CYBRD1, MBOAT2, BU678941, EMP2, AK026517, TNFRSF12A, FABP4, SLC9A9, CD38, SYTII, ARHGAP22, BTN2A2, PLA2G4C, POLE4 , SYTll, IL1RN, LGP2, MS4A3 and PDLIM4 and further evaluated in steps c) to e). 6. The method according to any one of claims 1 to 5, characterized in that the amount of gene products is determined by reverse transcribing mRNA to produce cDNA, and subjecting the cDNA under a real-time polymerase chain reaction and / or under a hybridization test. A method according to claim 6, characterized in that said hybridization test is a microarray test or a microspheres test. 8. Method according to one of claims 1 to 5, characterized in that the amount of gene products by using • t ·········································································································································································································· 9. microarray which has immobilized on its surface probes for the genes PHLDB3, FABP4, ABCG2, FBN2, SP0CD1 and SLAMF1 and wherein said microarray comprises at least 10%, preferably at least 20%, more preferably at least 30% of the total number of probes [ which] are probes for the genes PHLDB3, FABPl, ABCG2, FBN2, SPOCD1 and SLAMF1. 10. Microarray which has immobilized on its surface probes for genes, wherein said microarray at least 20%, preferably at least 40%, more preferably at least 60% of the total number of probe probes for the genes PHLDB3, MARCKS, LOC124220, FBN2, S100A10, BAU , SLAMF1, AOAH, EPSTI1, ABCG2, SPOCD1, LOC541471, ITGAD, RELB, DHRS9, CENTD3, IL4I1, GPIBA, S100A4, EHF, BTN2A2, LY75, PPFIBPl, H2AFY2, CYBRD1, MBOAT2, BU678941, EMP2, AK026517, TNFRSF12A, FABP4 , SLC9A9, CD38, SYTII, ARHGAP22, BTN2A2, PLA2G4C, POLE4, SYTII, ILlRN, LGP2, MS4A3 or PDLIM4. 11. microarray according to claim 9 or 10, characterized in that it additionally comprises probes for at least five, preferably at least ten, more preferably at least 15 normalizing genes selected from Table B. Microarray according to one of Claims 9 to 11, characterized in that it has a surface which is at least partially coated with a phenolic resin polymer having a functionality of from 6 to 15, preferably from 7 to 10, particularly preferably 8. 13. Kit containing probes for the genes PHLDB3, FABP4, ABCG2, FBN2, SPOCD1 and SLAMF1. 14. Kit according to claim 13, characterized in that it additionally probes for at least five, preferably at least six, in particular all of the genes MARCKS, LOC124220, S100A10, BAU, AOAH, EPSTIl, LOC541471, ITGAD, RELB, DHRS9, CENTD3, IL4I1, GPlBA, S100A4, EHF, BTN2A2, LY75, PPFIBP1, H2AFY2, CY- later • fl ························································································ ···················································································································································································································································································································· CD38, SYT11, ARHGAP22, BTN2A2, PLA2G4C, P0LE4, SYT11, ILIRN, LGP2, MS4A3 and PDLIM4. 15. Kit according to claim 13 or 14, characterized in that it further comprises probes of at least five, preferably of at least ten, more preferably of at least 15 normalizing genes selected from Table B. SUBSEQUENT