COMPLEMENTOME ASSAY
20230384322 · 2023-11-30
Inventors
- Paul BISHOP (Greater Manchester, GB)
- Simon CLARK (Baden-Wurttemberg, DE)
- Richard UNWIN (Greater Manchester, GB)
Cpc classification
International classification
Abstract
Methods of identifying subjects having complement-related disorders, or at risk of such disorders, are disclosed. Also disclosed are methods for selecting subjects for treatment with complement-targeted therapies, and methods of treatment of subjects with such therapies.
Claims
1.-26. (canceled)
27. A method of treating a macular degeneration in a subject, the method comprising: (a) determining in a blood-derived or liver sample obtained from the subject the level of one or more of FHR1, FHR2, FHR3, and/or FHR5, optionally in combination with FHR4, FHL-1, and/or FH; (b) determining that the subject has or is likely to develop a macular degeneration if the level of the protein(s) in (a) is elevated as compared to the level of that protein(s) in blood or liver tissue in a control subject that does not have a macular degeneration; and (c) treating the subject with a therapeutic agent that comprises or encodes a polypeptide comprising an amino acid sequence with at least 85% sequence identity to SEQ ID NO:146, wherein the polypeptide has a total length of 450 amino acids or fewer; and/or treating the subject with a nucleic acid agent that reduces expression of one or more of FHR1, FHR2, FHR3, FHR4, and/or FHR5.
28. The method according to claim 27, wherein the macular degeneration is selected from Age-related Macular Degeneration (AMD), Geographic Atrophy (‘dry’ or non-exudative AMD), early AMD, early onset macular degeneration (EOMD), intermediate AMD, late/advanced AMD, ‘wet’ (neovascular or exudative) AMD, choroidal neovascularisation (CNV), retinal dystrophy, and autoimmune uveitis.
29. The method according to claim 27, wherein the nucleic acid agent is an siRNA, miRNA, shRNA, antisense oligonucleotide, or gapmer.
30. The method according to claim 27, wherein the level of the one or more protein(s) is determined by mass spectrometry.
31. The method according to claim 27, wherein step (a) comprises: (i) digesting at least one of the protein(s) in the sample obtained from the subject with endoproteinase GluC to obtain one or more peptides; (ii) performing mass spectrometry to determine the presence and/or level of the one or more peptides; and (iii) using the results of (ii) to determine if the level of the protein(s) is elevated.
32. The method according to claim 27, wherein step (a) comprises determining the level of two or more of FHR1, FHR2, FHR5 and/or FHR3.
33. The method according to claim 32, wherein step (a) further comprises determining the level of FHR4.
34. The method according to claim 27, wherein the method further comprises determining the level of FHL-1 and/or FH, and optionally determining that the subject has or is likely to develop a macular degeneration if the level of FHL-1 is elevated as compared to the level of FHL-1 in blood from a control subject that does not have a macular degeneration.
35. The method according to claim 27, wherein the method comprises determining the level of: (i) FHR1 and FHR2; (ii) FHR2 and FHR3; (iii) FHR1 and FHR3; (iv) FHR1, FHR2, and FHR3; (v) FHR1, FHR2, and FHR5; (vi) FHR1, FHR2, FHR3, and FHR4; (vii) FHR1, FHR2, FHR3, and FHR5; (viii) FHR1, FHR2, FHR3, FHR4, and FHR5; or (ix) any of (i) to (viii) above in combination with FHL-1 and/or FH.
36. A method of treating a macular degeneration in a subject, the method comprising administering to the subject a therapeutic agent that comprises or encodes a polypeptide comprising an amino acid sequence with at least 85% sequence identity to SEQ ID NO:146, wherein the polypeptide has a total length of 450 amino acids or fewer; and/or administering to the subject a nucleic acid agent that reduces expression of one or more of FHR1, FHR2, FHR3, FHR4, and/or FHR5; wherein the subject has been determined to have or be likely to have a macular degeneration by: (a) determining in a blood-derived or liver sample obtained from the subject the level of one or more of FHR1, FHR2, FHR3, and/or FHR5, optionally in combination with FHR4, FHL-1 and/or FH; (b) determining that the subject has or is a likely to have a macular degeneration if the level of the protein(s) in (a) is elevated as compared to the level of that protein(s) in blood or liver tissue in a control subject that does not have a macular degeneration.
37. The method according to claim 36, wherein the macular degeneration is selected from Age-related Macular Degeneration (AMD), Geographic Atrophy (‘dry’ or non-exudative AMD), early AMD, early onset macular degeneration (EOMD), intermediate AMD, late/advanced AMD, ‘wet’ (neovascular or exudative) AMD, choroidal neovascularisation (CNV), retinal dystrophy, and autoimmune uveitis.
38. The method according to claim 36, wherein the nucleic acid agent is an siRNA, miRNA, shRNA, antisense oligonucleotide, or gapmer.
39. The method according to claim 36, wherein step (a) comprises determining the level of two or more of FHR1, FHR2, FHR5, and/or FHR3.
40. The method according to claim 39, wherein step (a) further comprises determining the level of FHR4.
41. The method according to claim 36, wherein the method further comprises determining the level of FHL-1 and/or FH, optionally determining that the subject has or is likely to develop a macular degeneration if the level of FHL-1 is elevated as compared to the level of FHL-1 in blood in a control subject that does not have a macular degeneration.
42. The method according to claim 36, wherein the method comprises determining the level of: (i) FHR1 and FHR2; (ii) FHR2 and FHR3; (iii) FHR1 and FHR3; (iv) FHR1, FHR2, and FHR3; (v) FHR1, FHR2, and FHR5; (vi) FHR1, FHR2, FHR3, and FHR4; (vii) FHR1, FHR2, FHR3, and FHR5; (viii) FHR1, FHR2, FHR3, FHR4, and FHR5; or (ix) any of (i) to (viii) above in combination with FHL-1 and/or FH.
43. The method according to claim 36, wherein the level of the one or more protein(s) is determined by mass spectrometry.
44. The method according to claim 36, wherein step (a) comprises: (i) digesting at least one of the protein(s) in the sample obtained from the subject with endoproteinase GluC to obtain one or more peptides; (ii) performing mass spectrometry to determine the presence and/or level of the one or more peptides; and (iii) using the results of (ii) to determine if the level of the protein(s) is elevated.
Description
FIGURES
[0701] Embodiments and experiments illustrating the principles of the invention will now be discussed with reference to the accompanying figures in which:
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EXAMPLES
Example 1: Generation of Peptides from Complement Proteins for Mass Spectrometry
[0727] GluC digestion was performed on FH, FHL-1, FHR1-5, FI, C3, C3b and C3b breakdown products to achieve distinct peptides for mass spectrometry. GluC digestion is described in Example 2.2.
[0728] Peptides that can be used to detect each protein or protein fragment are set out in Tables 1-4 below.
TABLE-US-00004 TABLE 1 Distinct FH family peptides after GluC digestion. SEQ ID Protein Peptide Sequence Mass No: Factor H VTYKCFE 888.4051 20 FHL1 NGWSPTPRCIRVSFTL 1832.9355 21 FHR1 ATFCDFPKINHGILYDEE 2110.9669 22 FHR2 RGWSTPPKCRSTISAE 1774.8784 23 and AMFCDFPKINHGILYDEE 2140.9598 24 FHR3 VACHPGYGLPKAQTTVTCTE 2074.9816 25 FHR4 YQCQSYYE 1082.4015 26 FHR5 RGWSTPPICSFTKGE 1664.7980 27
[0729] The series of proteolytic events leading to the generation, breakdown and inactivation of C3 are shown in
TABLE-US-00005 TABLE 2 Peptide sequences for MS resulting from GluC digestion of C3, C3b and breakdown products. Contained SEQ Peptide in C3b ID Peptide sequence products No: C3.1 GTAFVIFGIQDGE C3 + C3b + 28 iC3b + C3c C3.2 LRRQHARASHLG C3 only 29 LARSNLDE C3.3 LRRQHARASHLGLAR C3a only 30 C3.4 LNLDVSLQLPSR C3 + C3b 31 SSKITHRIHWE C3.5 LNLDVSLQLPSR iC3b + C3dg + C3d 32 C3.6 RLGRE C3 + C3b + iC3b 33 C3.7 SSKITHRIHWE C3f 34 C3.8 SASLLR C3f 35 C3.9 RLGR C3c 36 C3.10 HLIVTPSGCGE C3d 37
TABLE-US-00006 TABLE 3 Methodology for determining concentration of all C3/C3b breakdown products using GluC digestion peptides of Table 2. Protein or fragment Peptide(s) C3 (total) C3.1 C3 only C3.2 C3a C3.3 C3b C3.4-C3.2 iC3b C3.6-C3.4 C3f C3.7 or C3.8 C3c C3.9 C3dg C3.5-C3.10-iC3b [C3.6-C3.4] C3d C3.10
TABLE-US-00007 TABLE 4 Alternative peptides for C3.1 resulting from GluC digestion, to measure total C3 content. SED Peptide Mass Position Peptide sequence ID No. C3.1.1 6957.8210 463-523 AKIRYYTYLIMNKGRLLKAGRQVREPGQDLV 61 VLPLSITTDFIPSFRLVAYYTLIGASGQRE C3.1.2 5778.9734 321-372 RSGIPIVTSPYQIHFTKTPKYFKPGMPFDLMV 62 FVTNPDGSPAYRVPVAVQGE C3.1.3 5650.1364 97-146 KVVLVSLQSGYLFIQTDKTIYTPGSTVLYRIFT 63 VNHKLLPVGRTVMVNIE C3.1.4 3904.1017 373-408 DTVQSLTQGDGVAKLSINTHPSQKPLSITVRT 64 KKQE C3.1.5 3861.1628 565-599 GDHGARVVLVAVDKGVFVLNKKNKLTQSKI 65 WDVVE C3.1.6 3807.7645 600-637 KADIGCTPGSGKDYAGVFSDAGLTFTSSSG 66 QQTAQRAE C3.1.7 3263.6357 414-442 QATRTMQALPYSTVGNSNNYLHLSVLRTE 67 C3.1.8 2845.4609 24-50 AHDAQGDVPVTVTVHDFPGKKLVLSSE 68 C3.1.9 2819.4705 150-175 GIPVKQDSLSSQNQLGVLPLSWDIPE 69 C3.1.10 2691.3425 524-549 VVADSVWVDVKDSCVGSLVVKSGQSE 70 C3.1.11 2618.3261 296-320 DLVGKSLYVSATVILHSGSDMVQAE 71 C3.1.12 2511.2904 51-73 KTVLTPATNHMGNVTFTIPANRE 72 C3.1.13 2108.1378 78-96 KGRNKFVTVQATFGTQVVE 73 C3.1.14 1992.1480 278-295 VVLSRKVLLDGVQNPRAE 74 C3.1.15 1827.9414 448-462 TLNVNFLLRMDRAHE 75 C3.1.16 1769.8923 176-189 LVNMGQWKIRAYYE 76 C3.1.17 1745.9386 1-15 SPMYSIITPNILRLE 77 C3.1.18 1738.9036 550-564 DRQPVPGQQMTLKIE 78 C3.1.19 1623.9348 231-244 VTITARFLYGKKVE 79 C3.1.20 1352.6612 245-257 GTAFVIFGIQDGE 80 C3.1.21 1138.5335 219-226 KFYYIYNE 81 C3.1.22 1135.5146 190-199 NSPQQVFSTE 82 C3.1.23 954.5862 265-272 SLKRIPIE 83 C3.1.24 853.4221 205-211 YVLPSFE 84 C3.1.25 841.4657 258-264 QRISLPE 85 C3.1.26 826.4007 638-645 LQCPQPAA 86 C3.1.27 785.4171 212-218 VIVEPTE 87 C3.1.28 591.2938 19-23 TMVLE 88 C3.1.29 570.3125 443-447 LRPGE 89 C3.1.30 509.2485 74-77 FKSE 90
[0730] GluC digestion of Factor I (FI) produced the candidate peptides in Table 5 for MS analysis. SEQ ID NO:45 to 56 and 155 contain 8-21 amino acids and are a good length for MS analysis.
TABLE-US-00008 TABLE 5 Peptide sequences resulting from GluC digestion of Fl. SEQ Peptide Mass Position Peptide sequence ID NO: 1 3996.7183 510-548 CAGTYDGSIDACKGDSGGPLVCMDANN 38 VTYVWGVVSWGE 2 3994.8853 57-92 GTCVCKLPYQCPKNGTAVCATNRRSFPTYCQQKSLE 39 3 3467.7211 555-583 FPGVYTKVANYFDWISYHVGRPFISQYNV 40 4 3397.6804 150-180 ANVACLDLGFQQGADTQRRFKLSDLSINSTE 41 5 3388.6605 446-475 LPRSIPACVPWSPYLFQPNDTCIVSGWGRE 42 6 3155.5773 31-56 KKCLAKKYTHLSCDKVFCQPWQRCIE 43 7 2991.2861 254-281 LCCKACQGKGFHCKSGVCIPSQYQCNGE 44 8 2531.2455 129-149 VKLVDQDKTMFICKSSWSMRE 45 9 2068.0320 489-505 VKLISNCSKFYGNRFYE 46 10 1805.8309 93-109 CLHPGTKFLNNGTCTAE 47 11 1698.7969 420-434 NYNAGTYQNDIALIE 48 12 1605.7867 110-124 GKFSVSLKHGNTDSE 49 13 1297.5729 291-303 VGCAGFASVTQEE 50 14 1168.272 291-302 VGCAGFASVTQE 155 15 1295.6082 435-445 MKKDGNKKDCE 51 16 1191.6156 411-419 YVDRIIFHE 52 17 1166.5557 181-190 CLHVHCRGLE 53 18 1121.5738 480-488 RVFSLQWGE 54 19 978.4448 306-314 ILTADMDAE 55 20 955.4731 19-26 KVTYTSQE 56 21 736.3182 282-288 VDCITGE 57 22 647.2817 549-554 NCGKPE 58 23 520.2613 191-195 TSLAE 59 24 505.2252 476-479 KDNE 60
Example 2: Mass Spectrometry
2.1 Preparation of Stable Isotopic Standards (SIS) Spiking Solution
[0731] High purity heavy-labelled synthetic standards, with S-carboxymethylated (CAM) cysteine residues, were obtained (Cambridge Research Biochemicals, Cambridge, UK) and diluted to 1 μg/μL with 50:50 acetonitrile:water+0.1% formic acid (Table 6).
[0732] A mixed SIS solution was prepared by firstly diluting stock solution of FHL-1, FHR1, FHR2, FHR3, FHR4 and FHR5 by tenfold (no dilution of CFH stock was required), then adding the appropriate amounts of each individual diluted solution to a final volume of 200 μL in 0.1% TFA. This was then stored at −80° C. in 5 μL aliquots for further dilution immediately prior to spiking.
[0733] Spiking solution was prepared immediately prior to sample addition by adding 195 μL 50:50 acetonitrile:water to a 5 μL aliquot of the mixed SIS solution. 2 μL of this was carefully added to each digested sample prior to drying down.
TABLE-US-00009 TABLE 6 Stock solutions of stable isotopic standards (SIS) at 1 ug/MI. The residues in bold were chosen to carry a stable-heavy isotype to enable quantitation. Lower case ‘c’ denotes a S-carboxymethylated (CAM) cysteine residue. Residue in bold type contained an isotopically heavy amino acid, where K(+8), R(+10), F(+10) and Y(+10). Net Solvent Pro- Peptide MW, Purity, Content, Volume, Conc, tein Sequence g % % μL pmol/μL CFH VTYKcFE 953.4 98.6 72.6 716 1050 FHL- NGWSPTPR 1900 97.4 78.9 768 526.3 1 cIRVSFTL FHR1 ATFcDFPKI 2178 100.0 80.7 807 459.1 NHGILYDEE FHR2 RGWSTPPK 1845.9 100.0 55.5 555 541.7 RESTISAE FHR3 VACHPGYG 2207.1 98.4 75.0 738 453.1 LPKAQTTV TcTE FHR4 YQCQSYYE 1149.7 97.6 84.1 821 869.8 FHR5 RGWSTPPI 1739.8 95.6 74.0 707 574.8 CSFTKGE
2.2 Preparation of Samples for Analysis by LC-MS/MS
[0734] Frozen plasma samples were allowed to thaw to room temperature before being vortexed hard for 5 minutes to dissolve any soluble material, then centrifuged at 13,300g for 30 min to settle any insoluble material.
[0735] To a 5 μL plasma aliquot (equivalent to approximately 350 μL protein), 90 μL of 50 mM ammonium bicarbonate (pH 7.8), 2 μL of ProteaseMAX™ (Promega, Southampton, UK) solution (1% w/v in 50 mM ammonium bicarbonate) and 1 μL of 500 mM dithiothreitol prepared in 50 mM ammonium bicarbonate was added. This was vortexed briefly to mix, then given a pulse spin before incubating at 56° C. for 25 min.
[0736] After cooling to room temperature, 3 μL 500 mM iodoacetamide (prepared in 50 mM ammonium bicarbonate) was added. This was vortexed briefly to mix, then given a pulse spin before incubating at room temperature and in the dark for 15 min.
[0737] A further 1 μL of ProteaseMAX solution (1% w/v in 50 mM ammonium bicarbonate) and 5 μL of 1 μg/uL endoproteinase GluC (Roche, Mannheim, Germany) were added. The mixture was vortexed briefly, then given a pulse spin before incubating for 16 hours at 25° C. with slight shaking (400 rpm).
[0738] To the digested peptide mix obtained, 6 μL 10% v/v trifluoroacetic acid (TFA) and 2 μL of SIS spiking solution were added, vortexed briefly to mix, then pulse spin. The solution was placed into an evaporator and dried. Finally the peptides were reconstituted in 50 μL 0.1% TFA and vortexed to dissolve any residue before centrifuging at 13,300g for 30 min to settle any insoluble/particulate material. Approximately 48 μL (taking care to leave behind any precipitated material) was transferred to a LC autosampler vial for subsequent analysis by LC-MS/MS.
2.3 LC-SRM/MS Analysis of Plasma Digests
[0739] SRM analyses of plasma digests were performed on a 6495 triple quadrupole mass spectrometer with iFunnel-equipped electrospray ion source (Agilent, Santa Clara, CA, USA) coupled to an Infinity 1200 Series liquid chromatography system consisting of 1290 autosampler, 1260 Quat Pump VL pump and TCC column oven modules (Agilent, Santa Clara, CA, USA). Samples were injected directly (4 μL) onto a C18 column (250 mm×2.1 mm i.d., Thermo Scientific Acclaim 120, 3 μm particle size) that was maintained at a column temperature of 50° C. Compounds were developed using a gradient elution of increasing acetonitrile concentration with Buffer A consisting of Water+0.1% formic acid and Buffer B being Acetonitrile+0.1% formic acid. The flow rate was maintained at 250 μL/min with an initial composition of 5% Buffer B.
[0740] The following gradient elution profile was used to separate the peptides (time: % B): 0 min: 5% B; 2 min: 5% B; 3 min: 12% B; 12 min: 15% B; 15 min: 20% B; 30 min: 25% B; 31 min: 90% B; 39 min: 90% B; 40 min: 5% B; 49 min: 5% B.
[0741] Optimized SRM settings were determined using SIS solutions and are provided in Table 7.
TABLE-US-00010 TABLE 7 SRM transitions and optimal collision energies for FH family peptides (Quantitation ions in bold). Precursor Product Collision ion ions energy, Protein Peptide Sequence m/z m/z eV CFH VTYKcFE (Light) 473.7 583.3, 16, 16, 16 847.4, 746.3 CFH VTYKcFE (Heavy) 477.7 591.3, 16, 16, 16 855.4, 754.3 FHL-1 NGWSPTPRcIRVSFTL 631.2 723.9, 19, 19, 19 (Light) 860.5, 767.4 FHL-1 NGWSPTPRcIRVSFTL 634.3 728.9, 19, 19, 19 (Heavy) 865.5, 772.4 FHR1 ATFcDFPKINHGILYDEE 724.2 925.6, 20, 16, 20 (Light) 1011.9, 947.1 FHR1 ATFcDFPKINHGILYDEE 727.2 930.6, 20, 16, 20 (Heavy) 1016.9, 952.1 FHR2 RGWSTPPKcRSTISAE 459.1, 539.2, 8, 26 (Light) 611.8 798.9 FHR2 RGWSTPPKcRSTISAE 462.6, 543.9, 8, 26 (Heavy) 616.3 806.0 FHR3 VACHPGYGLPKAQTTVTCTE 730.7 1022.4, 16, 18 (Light) 971.7 FHR3 VACHPGYGLPKAQTTVTCTE 736.7 1031.4, 16, 18 (Heavy) 980.7 FHR4 YQCQSYYE 570.7 830.3, 11, 10, 14 (Light) 993.1, 311.1 FHR4 YQcQSYYE 575.7 840.3, 11, 10, 14 (Heavy) 1003.1, 311.1 FHR5 RGWSTPPICSFTKGE 575.2 828.4, 16, 15, 20 (Light) 895.5, 588.3 FHR5 RGWSTPPICSFTKGE 581.2 836.4, 16, 15, 20 (Heavy) 905.5, 598.3
TABLE-US-00011 TABLE 8 Peptides and transitions for quantitation of C3/C3b breakdown products. Pep- Contained tide Sequence in . . . Transitions C3.1 GTAFVIFGIQDGE C3 + C3b + 569.0/483.2 iC3b + C3c 569.0/654.3 569.0/801.4 C3.2 LRRQHARASHLG C3 only 384.2/431.6 LARSNLDE 384.2/510.4 461.0/503.3 C3.3 LRRQHARASHLGLAR C3a only 291.2/304.3 291.2/395.8 436.3/598.7 C3.4 LNLDVSLQLPSRS C3 + C3b 546.8/578.7 SKITHRIHWE 683.2/797.1 683.2/834.9 C3.5 LNLDVSLQLPSR iC3b + 677.9/1014.4 C3dg + 677.9/359.1 C3d 677.9/800.2 C3.6 RLGRE C3 + 251.3/175.1 C3b + 251.3/232.1 iC3b 251.3/345.2 C3.7 SSKITHRIHWE C3f 349.3/354.2 349.3/436.4 349.3/489.8 C3.8 SASLLR C3f 323.7/159.1 323.7/288.2 323.7/488.3 C3.9 RLGR C3c 251.3/175.1 251.3/232.1 251.3/345.2 C3.10 HLIVTPSGCGE C3d 585.3/251.1 585.3/394.5 585.3/404
[0742] In order to protect the source region from unwanted contaminants, a switching valve located between the column and source was diverted to the waste position at points in the chromatogram when the analyte peptides were not eluting. This allowed for six windows (two of the peptides, FHR-2 and FHL-1, eluted within the same window) of acquisition, of approximately one minute each, to be acquired with the column on-line to the mass spectrometer. SRM data was processed using a dedicated project in Skyline (v19.1.0.193; www.skyline.ms).
2.4 Results
[0743] FH Family Proteins
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[0746] Lower limits of quantitation were defined as plasma concentrations of FH=25 nM, FHL-1=0.25 nM, FHR-1=2 nM, FHR-2=1 nM, FHR-3=1 nM, FHR-4=4 nM and FHR-5=3 nM.
[0747] C3 and C3 Breakdown Products
[0748] Synthetic versions of the peptides in Table 2 were synthesised to confirm and optimise their detection by MS to confirm that they could be quantified in a linear manner, and to demonstrate that they could be detected at endogenous levels in a serum or plasma sample. This is shown by
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[0750] C3b breakdown was further analysed in an in vitro assay. C3b was incubated along with FI and a fragment of cofactor CR1, selected over FH as CR1 drives the reaction to cleavage of iC3b to C3c+C3dg, whereas FH will only support cleavage of C3b to iC3b. Sequential samples were taken from the reaction and stopped by boiling.
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[0752] These data demonstrate that C3/C3b breakdown can be measured in a quantitative manner using GluC-derived peptides and MS. This enables the presence and levels of complement proteins to be detected in complement-related diseases such as AMD, as well as providing information as to successful treatment outcomes.
[0753] A single assay which can measure all FH family, C3 fragments and FI proteins allows for the simultaneous analysis of all key proteins in the complement amplification loop from just one sample and with efficient throughput.
Example 3: Detection of the Complementome in AMD Patients
3.1 Sample Collection and Processing
[0754] Plasma samples were collected during the Cambridge AMD study; a case-control study with subjects recruited from the southeast and northwest of England between 2002 and 2006. The original study and its results are described in Yates et al., (2007). N. Engl. J. Med. 357, 553-561. All 246 affected subjects had advanced, end-stage AMD (choroidal neovascularization and/or geographic atrophy). 166 control subjects were spouses, partners or friends of index patients. Blood samples were obtained at the time of interview; EDTA and lithium-heparin plasma samples were used for the measurement of CFH, FHL-1 and the FHR proteins.
[0755] Analysis of plasma samples by Mass Spectrometry was performed as per Example 2 to determine levels of CFH, FHL-1 and FHR proteins. Samples were prepared for LC-MS/MS analysis by digestion and addition of SIS spiking solution as described in (2.1 and 2.2). Samples were then analysed by LC-SRM/MS as described in (2.3).
[0756] All statistical analyses were performed using GraphPad Prism (v8.4.3).
3.2 Results
[0757] The data was analysed for evidence of correlation between the levels of the studied proteins. All Pearson correlation coefficients were found to be weaker than +/−0.55. It was therefore concluded that there is no strong linear relationship between different protein levels and little pair-wise correlation. Notably, inspection of the scatterplots did not reveal evidence of nonlinear relationship between variables. The relevant correlation matrix is shown in
[0758] Protein levels were then compared between AMD cases (n=399; subjects having CNV, geographic atrophy or a mixed phenotype) and controls (n298). Non-parametric tests (Mann-Whitney test) for the absolute protein levels were performed and statistically significant differences were detected between cases and controls for FHR1, FHR2, FHR3, FHR4, FHR5 and FHL-1 (
[0759] The association of advanced AMD with each of the FH, FHL-1 and five FHR levels was assessed via Wald tests using linear regression models adjusted for sex, age and the first two genetic principal components (as estimated within the IAMDGC study). The association of levels with advanced AMD was also reported via odds ratio (OR) expressed as per one standard deviation (SD) change of log-levels using logistic regression models adjusted for sex, age and the first two genetic principal components. The results are displayed in Table 1.
TABLE-US-00012 TABLE 1 Demographics of study samples and association analyses between AMD and circulating FH, FHL-1, FHR-1 to FHR-5 protein levels. Controls Cases N 252 352 Age, ys (SD) 75.2 (7.9) 73.9 (8.3) Male (%) 39.3 45.7 AMD phenotype CNV only 218 GA only 73 Mixed 61 OR (95% Cl).sup.b Mean FH levels, 737.3 736.5 nM (95% Cl) (718.2-756.5) (721.3-751.6) Association with 0.005, 0.23, 0.982 1.01 AMD, Beta, SE, P.sup.a (0.02, 0.23, 0.936) (0.86-1.20) Mean FHL-1 levels, 10.4 11.3 nM (95% Cl) (10.1-10.8) (11.0-11.7) Association with 0.08, 0.02, 1.4 × 10.sup.−3 1.35 AMD, Beta, SE, P.sup.a (0.08, 0.02, 4.9 × 10.sup.−4) (1.14-1.60) Mean FHR-1 levels, 31.2 38.4 nM (95% Cl) (29.4-32.9) (37.0-39.8) Association with 7.22, 1.12, 2.1 × 10.sup.−10 1.81 AMD, Beta, SE, P.sup.a (7.21, 1.12, 2.4 × 10.sup.−10) (1.47-2.24) Mean FHR-2 levels, 45.3 55.3 nM (95% Cl) (43.1-47.6) (53.2-57.4) Association with 0.71, 0.12. 1.9 × 10.sup.−9 1.66 AMD, Beta, SE, P.sup.a (0.74, 0.12, 6.0 × 10.sup.−10) (1.38-1.98) Mean FHR-3 levels, 24.1 28.9 nM (95% Cl) (21.7-26.5) (27.1-30.8) Association with 0.55, 0.13, 4.4 × 10.sup.−5 1.54 AMD, Beta, SE, P.sup.a (0.59, 0.13, 1.4 × 10.sup.−5) (1.29-1.84) Mean FHR-4 levels, 46.1 53.8 nM (95% Cl) (42.7-49.6) (50.5-57.1) Association with 0.53, 0.17, 2.1 × 10.sup.−3 1.27 AMD, Beta, SE, P.sup.a (0.56, 0.17, 1.3 × 10.sup.−3) (1.08-1.50) Mean FHR-5 levels, 25.5 27.9 nM (95% Cl) (24.5-26.5) (27.0-28.9) Association with 0.09, 0.03, 1.9 × 10.sup.−4 1.38 AMD, Beta, SE, P.sup.a (0.10, 0.03, 1.9 × 10.sup.−4) (1.16-1.63) .sup.aWald tests using linear regression models; adjusted P-values for sex, age and first two genetic principal components as estimated in Fritsche et al..sup.2 are displayed in parentheses; .sup.bOdds ratio (OR) of advanced disease expressed as per standard deviation change of log-levels using logistic regression models adjusted for sex, age and the first two genetic principal components. AMD = age-related macular degeneration; CNV = choroidal neovascularization; GA = geographic atrophy; SE = standard error; CI = confidence interval.
[0760] The data were examined to determine to what extent the clinical outcome (AMD or no AMD) could be predicted based on the different protein level values. Multiple logistic regression analysis was used for this purpose and the findings for different models are shown in
[0761] Genotype Data and Genome-Wide Association Analysis
[0762] Genome-wide association analyses were performed of the protein levels that were found to be elevated in advanced AMD cases (i.e., FHL-1 and FHR-1 to FHR-5).
[0763] All individuals included in the study had been previously genotyped with a custom-modified Illunina HumanCoreExome array at the Centre for Inherited Disease Research (CIDR, Baltimore, Maryland, USA) and analysed within the International AMD Genomics Consortium (IAMDGC) GWAS (43,566 subjects; 16,144 advanced AMD cases and 17,832 controls of European ancestry in the primary analysis dataset). Quality control and genotype imputation using the 1000 Genomes Project (Abecasis et al., Nature 2012, 491, 56-65) reference panel were performed by the IAMDGC as described in Fritsche et al., Nature Genetics, 2016, 48, 134-143.
[0764] GWASs were performed for FH, FHL-1 and the five FHR levels (transformed to ensure normality) in controls only, using linear regression models adjusted for sex, age and the first two genetic principal components, and variants with Minor Allele Frequency, MAF≥1%. The GWASs were carried out using the EPACTS software (http://genome.sph.umich.edu/wiki/EPACTS, version 3.3.2) and Wald tests were performed on the variant genotypes coded as 0, 1 and 2 according to the number of minor alleles for the directly typed variants or allele dosages for the imputed variants. Manhattan and Q-Q plots were generated using the qqman R package (version 0.1.4). Regional plots of association were generated using LocusZoom.org. Finally, linkage disequilibrium (LD) measures (R.sup.2 and D′) were calculated using LDlink (https://ldlink.nci.nih.gov/), based on the European (EUR) population genotype data originated from the Phase 3 (Version 5) of the 1000 Genomes Project.
[0765] Remarkably, all GWASs of the five FHR protein levels in 252 controls showed a genome-wide significant (P≤5×10.sup.−8) peak at the CFH locus, see
[0766] FHR-3 showed a more polygenic profile, with genome-wide significant signals at rs113721756 on chromosome 10 (P-value=1.7×10.sup.−8), rs111260777 on chromosome 11 (P-value=1.5×10.sup.−9), rs117468955 on chromosome 12 (P-value=3.0×10.sup.−8), rs4790395 on chromosome 17 (P-value=3.6×10.sup.−8) and rs117115124 on chromosome 19 (P-value=2.5×10.sup.−8) in addition to the CFH locus. The strongest signal from the GWAS of FHL-1 levels was observed at rs200404865 on chromosome 13 (P-value=9.6×10.sup.−7), with the strongest signal at the CFH locus observed at intronic KCNT2 rs61820755 (P-value=5.3×10.sup.−6).
[0767] The CFH locus genome-wide significant regions from the analyses of FHR-1 to FHR-5 levels overlapped among the different levels, but showed nominally different top signals (i.e., intergenic CFHR1/CFHR4 rs149369377 for FHR-1 with P-value=2.6×10.sup.−43 and β=−18.2, synonymous CFHR2 rs4085749 for FHR-2 with P-value=6.3×10.sup.−33 and β=−1.5, intronic CFH rs70620 for FHR-3 with P-value=1.5×10.sup.−25 and β=2.0, intergenic CFHR1-CFHR4 rs12047098 for FHR-4 with P-value=1.1×10.sup.−17 and β=−1.7, and intronic KCNT2 rs72732232 for FHR-5 with P-value=2.2×10.sup.−10 and β=−0.5). These top signals are not in high LD with each other, except for rs4085749 of FHR-2 and rs12047098 of FHR-4 (R.sup.2=0.83, D′=0.95).
[0768] Next, it was assessed whether the GWAS top signals of FHR-1 to FHR-5 protein levels were in LD with any of the independently AMD-associated variants at the CFH locus reported by the IAMDGC GWAS, which also included the Cambridge samples analysed in this study (i.e., intronic CFH rs10922109 [1.1]; intronic CFH rs570618 [1.2], proxy for Y402H; CFH R1210C, rs121913059 [1.3]; intergenic rs148553336 [1.4], 8 kb upstream CFH/35 kb downstream KCNT2; intronic KCNT2 rs187328863 [1.5]; intergenic rs61818925 [1.6], 14 kb downstream CFHR1/156 kb upstream CFHR4; intronic CFH rs35292876 [1.7]; intronic CFHR5 rs191281603 [1.8]; see Table 2 and
[0769] The top signal for FHR-1 was in modest LD with the top AMD-associated variant 1.1 (R.sup.2=0.30) and low LD with the proxy for Y402H 1.2 (R.sup.2=0.12); the top signal for FHR-2 was in modest LD with 1.1 (R.sup.2=0.35) and 1.6 (R.sup.2=0.36), and low LD with 1.2 (R.sup.2=0.16); similarly for the top signal of FHR-4 (R.sup.2 equal to 0.38, 0.42 and 0.16 with 1.1, 1.6 and 1.2, respectively); low LD was seen with 1.1, 1.2 and 1.6 (R.sup.2 equal to 0.16, 0.12 and 0.11, respectively) for the top signal of FHR-3, while the top signal of FHR-5 was in low/modest LD with 1.4 (R.sup.2=0.26).
[0770] Furthermore, genome-wide significant associations were observed at the top IAMDGC variant rs10922109 (1.1) with P-values 8.6×10.sup.−21, 2.9×10.sup.−10, 2.2×10.sup.−16 and 1.7×10.sup.−9 for FHR-1, FHR-2, FHR-3 and FHR-4, respectively, at the proxy for Y402H 1.2 with P-values 2.0×10.sup.−11 and 1.8×10.sup.−12 for FHR-1 and FHR-2, respectively, and at the variant 1.6 with P-values 1.8×10.sup.−11 and 2.4×10.sup.−9 for FHR-2 and FHR-4, respectively. All these genetic associations showed direction of allelic effect on levels concordant with that on disease as estimated in the IAMDGC GWAS study (Table 2,
[0771] Mendelian Randomization Estimates of the Effects of Circulating Levels of Complement Regulatory Proteins on Susceptibility to AMD
[0772] A Mendelian randomization approach was used to test if genetically proxied FHR protein levels are associated with risk of AMD.
[0773] Independent (LD, R2<0.001) genetic variants associated with the exposure were selected as instrumental variables (a protein at a time) at genome-wide significance level in controls only. If a single instrument was available, the ratio of coefficients method was used, also known as the Wald method, to estimate the effect of genetically proxied protein levels on the disease risk. The Wald ratio for a single genetic variant as instrumental variable is defined as its genetic association with the outcome (i.e. risk of AMD) over the genetic association with the exposure (i.e. protein level). Using a one-sample approach, the genetic association was derived with the exposure from the GWASs based on linear regression models for the FHR protein levels conducted on the Cambridge controls only (n=252). The genetic associations with the outcome were obtained from the GWAS based on a logistic regression model with AMD status as outcome conducted on the Cambridge samples (252 controls and 353 cases). If multiple instruments were available for a protein, the inverse-variance weighted (IVW) method was used under a fixed-effect model. Instrument strength was evaluated using R2 as the proportion of the variance of the protein explained by the genetic variant(s). The Mendelian randomization analysis was performed using the MendelianRandomization (version 0.4.2) and TwoSampleMR (version 0.5.5) R packages.
[0774]
[0775] The variance of the FHR protein levels explained by the corresponding genetic instrument(s) varied from 15% for FHR5 to 73% for FHR3. The Mendelian randomization estimates were statistically significant and of concordant direction with the observational OR estimates for FHR-1, FHR-2, FHR-4 and FHR-5, providing evidence in support of a causal effect (
[0776] As such, while these data strongly support a causal role of increased FHR-1, FHR-2, FHR4 and FHR-5, the consequences of the observed increase in FHL-1 and FHR-3 circulating levels in individuals with AMD remain less clear.
[0777] Applying a cut off for ‘high’ expression of FHR proteins according to the 90.sup.th percentile of the healthy controls group, it was calculated that ˜30% of AMD cases in this cohort displayed elevated levels of at least one FHR protein. This is consistent with the observation that around 34% of AMD patients carry an AMD risk variant at this locus. This is likely an underestimate, since our controls in this study contain individuals with AMD risk variants but do not (yet) have AMD.
[0778] Conclusions
[0779] Using 252 non-AMD controls to get insights into the genetic determinants of the circulating protein levels measured in this study, it was discovered that variants at the CFH locus regulate all five FHR protein levels (with genome-wide significant associations in our analyses of the FHR protein levels overlapping with the AMD-associated CFH region). Notably, established genetic associations with AMD risk at the non-coding variants 1.1, proxy for Y402H 1.2 and 1.6 translated into genetic associations at genome-wide significant level with FHR-1, FHR-2, FHR-3 and FHR-4 from the GWASs in our control group
[0780] The identification of the CFH locus as a cis protein quantitative trait locus (cis-pQTL) for the five FHR levels prompted the use of the available genetic data in a Mendelian randomization fashion to triangulate this evidence. For FHR-1, FHR-2, FHR-4 and FHR-5, the support provided by Mendelian randomization analyses for a potential casual role in susceptibility to AMD is striking, with Mendelian randomization estimates corroborating the preliminary evidence shown by the observational OR estimates (see Table 1).
[0781] This reframes our understanding of the aetiology of AMD, and the role of the non-coding risk variants on chromosome 1q31.3, demonstrating a prominent role for the FHR proteins. It also demonstrates that targeting (and lowering) of FHR proteins in the circulation as a viable therapeutic avenue for AMD, including systemic therapeutic strategies.
[0782] Identifying patients with risk factors for AMD will allow patients to avoid surgical procedures, especially in the early stages of disease before the loss of visual acuity, where therapeutic intervention may yield the most benefit. Patient stratification will be important as only a proportion of AMD patients are likely to suffer from FHR-mediated disease. However, as demonstrated above a patient's genetic-risk profile, coupled with measurements of their circulating FHR protein levels, is able to identify and stratify those patients most likely to benefit from such treatments, and to monitor their response to FHR-lowering agents.
TABLE-US-00013 TABLE 2 Single-variant association analyses for the 8 AMD independently associated variants at the CFH locus from the IAMDGC study with FH, FHL-1, FHR-1 to FHR-5 levels in 252 controls. IAMDGC dbSNP ID Association with levels in Cambridge controls.sup.a association (Chr:Position).sup.c FH FHL-1 FHR-1 FHR-2 FHR-3 FHR-4 FHR-5 signal Major/Minor IAMDGC OR MAF Beta Beta Beta Beta Beta Beta Beta number allele (MAF in Cambridge (SE) (SE) (SE) (SE) (SE) (SE) (SE) (direction.sup.b) (Imputation R.sup.2).sup.d controls) controls P P P P P P P 1.1 rs10922109 0.38 0.422 0.49 −0.10 −10.67 −0.75 −1.20 −1.0 −0.04 (−) (1:196704632) (0.426) (0.25) (0.02) (1.04) (0.11) (0.14) (0.17) (0.03) C/A 0.056 3.7 × 7.8 × 2.9 × 1.7 × 1.5 × 0.184 (1.00) 10.sup.−5 10.sup.−21 10.sup.−11 10.sup.−16 10.sup.−9 1.2 rs570618 2.38 0.357 0.27 0.05 8.19 0.85 0.16 0.62 0.10 (+) (1:196657064) (0.364) (0.26) (0.03) (1.17) (0.11) (0.16) (0.18) (0.03) G/T 0.296 0.046 2.0 × 1.8 × 0.304 6.8 × 7.8 × (1.00) 10.sup.−11 10.sup.−12 10.sup.−4 10.sup.−4 1.3 rs121913059 20.28 0 No control carrier observed; not analyzed (+) (1:196716375) (0.00014) C/T (Genotyped) 1.4 rs148553336 0.29 0.017 −2.29 −0.09 0.06 −1.99 0.33 0.74 −0.55 (−) (1:196613173) (0.009) (1.02) (0.10) (5.00) (0.48) (0.62) (0.72) (0.11) T/C (Genotyped) 0.025 0.353 0.990 4.6 × 0.603 0.302 6.3 × 10.sup.−5 10.sup.−7 1.5 rs187328863 2.27 0.013 1.12 0.06 0.75 1.13 −0.51 0.61 0.01 (+) (1:196380158) (0.028) (1.34) (0.13) (6.52) (0.64) (0.81) (0.94) (0.15) C/T 0.404 0.660 0.908 0.080 0.536 0.515 0.956 (0.83) 1.6 rs61818925 0.60 0.405 −0.42 0.001 0.99 −0.93 0.85 −1.12 −0.07 (−) (1:196815450) (0.385) (0.27) (0.03) (1.33) (0.12) (0.16) (0.18) (0.03) G/T 0.124 0.962 0.459 1.3 × 1.7 × 1.5 × 0.014 (0.87) 10.sup.−13 10.sup.−7 10.sup.−9 1.7 rs35292876 2.42 0.004 MAF <= 1%; not analyzed (+) (1:196706642) (0.009) C/T (Genotyped) 1.8 rs191281603 1.07 0.008 MAF <= 1%; not analyzed (+) (1:196958651) (0.006) C/G (0.42)
Example 4: Tumor Cell IDO Enhances Immune Suppression and Decreases Survival Independent of Tryptophan Metabolism in Glioblastoma
4.1 Abstract
[0783] Purpose: Glioblastoma (GBM) is an incurable primary brain tumor that has not benefited from immunotherapy to-date. Greater than 90% of GBM expresses the tryptophan (Trp) metabolic enzyme, indoleamine 2,3-dioxygenase 1 (IDO). This observation supported the historical hypothesis that IDO suppresses the antitumor immune response solely through a mechanism that requires intratumoral Trp depletion. However, recent findings led us to investigate the alternative hypothesis that IDO suppresses the anti-GBM immune response independent of its association with Trp metabolism.
[0784] Experimental Design: IDO-deficient GBM cell lines reconstituted with IDO wild-type or IDO enzyme-null cDNA were created and validated in vitro and in vivo. Microarray analysis was conducted to search for genes that IDO regulates, followed by the analysis of human GBM cell lines, patient GBM and plasma, and the TCGA database. Ex vivo cell co-culture assays, syngeneic and humanized mouse GBM models were used to test the alternative hypothesis.
[0785] Results: Non-enzymic tumor cell IDO activity decreased the survival of experimental animals and increased the expression of complement factor H (CFH) and its isoform, factor H like protein 1 (FHL-1) in human GBM. Tumor cell IDO increased CFH and FHL-1 expression independent of tryptophan metabolism. Increased intratumoral CFH and FHL-1 levels were associated with poorer survival among glioma patients. Similar to IDO effects, GBM cell FHL-1 expression increased intratumoral Tregs and MDSCs while it decreased overall survival in mice with GBM.
[0786] Conclusions: Our study reveals a newly non-metabolic IDO-mediated enhancement of CFH expression and provides a new therapeutic target in patients with GBM.
4.2 Translational Relevance
[0787] Since the ECHO-301 phase III clinical trial results were reported, questions have been raised as to why IDO enzyme inhibition fails to improve the survival of patients with cancer. In the current study, this question was addressed and it was confirmed that tumor cell IDO possesses activities that extend beyond tryptophan metabolism and suppress the anti-cancer immune response. This study discovered that non-metabolic IDO increases the expression of immunosuppressive complement factor H (CFH) expression and in-turn, suppressed the anti-tumor immune response and decreased the survival of experimental animals with brain tumors. High intratumoral CFH levels were associated with a substantial decrease in glioma patient survival. These findings help elucidate our understanding of clinical trial results that have targeted IDO enzyme activity to-date and provide a new target for improving immunotherapeutic efficacy in patients with malignant glioma.
4.3 Introduction
[0788] Glioblastoma (GBM) is the most common malignant primary central nervous system (CNS) cancer in adults (1). Despite an aggressive standard of care treatment that includes maximal surgical resection when possible, followed by tumor-targeted radiation and chemotherapy with temozolomide (TMZ), the prognosis remains dismal. Median survival for GBM is 14.6 months (2) with a five-year overall survival (OS) of ˜4.7% in the United States (3). These grim statistics provide compelling rationale to develop more effective treatments for patients with GBM.
[0789] Immune checkpoint blockade and chimeric antigen receptor (CAR) T cell treatment have improved the lifespan of patients diagnosed with select advanced cancers (4). Patients with GBM are among the malignancies that are uniquely unresponsive to cancer immunotherapy and have yet to benefit from this approach in accordance with all phase III clinical trials to-date (5-7). A contributing factor to the immune resistance of GBM cells is indoleamine 2, 3-dioxygenase 1 (IDO) that is frequently expressed in wild-type isocitrate dehydrogenase (IDH) GBM (8). IDO is canonically characterized as a rate-limiting immunosuppressive enzyme that converts the essential amino acid, tryptophan (Trp), into downstream metabolites that are collectively referred to as kynurenines (Kyn) (9). Tumor cell expression of IDO increases the intratumoral accumulation of immunosuppressive regulatory T cells (Tregs; CD4.sup.+CD25.sup.+FoxP3.sup.+) and decreases overall survival in experimental mice with brain tumors (10). Although GBM cells do not normally express IDO, its expression is induced by tumor-infiltrating T cells (11). Higher levels of GBM-infiltrating T cells are therefore associated with higher intratumoral IDO expression levels and an associated decreased overall survival of GBM patients. (11, 12). Since IDO is expressed among a wide variety of adult cancers (13), pharmacologic enzyme inhibitor treatment approaches have been evaluated for their potential to improve cancer patient survival outcomes (14, 15). There have been no objective survival benefits noted among randomized clinical trials evaluating this approach in patients with aggressive cancer to-date (16). This may be due to a combination of factors including (i) a requirement to inhibit IDO and other immunosuppressive pathways simultaneously (17, 18), (ii) age-dependent increases of IDO that are unresponsive to pharmacologic enzyme inhibition (19), and/or (iii) immunosuppressive IDO effects that are independent of its association with acting as a tryptophan metabolic enzyme (20).
[0790] Previous work in mice demonstrated that Tregs accumulate in IDO-expressing brain tumors despite the treatment with a potent blood brain barrier-penetrating pharmacologic IDO enzyme inhibitor (18). Also unexpectedly, IDO-mediated Trp metabolism was predominantly mediated by non-GBM cells rather than by the tumor cells in the brain (21). These findings collectively challenge the historical hypothesis that tumor cell IDO increases Tregs and decreases survival through a mechanism that solely depends on Trp metabolism and motivated us to explore the alternative hypothesis that GBM cell IDO suppresses antitumor immunity independent of its enzyme function(s).
4.4 Materials and Methods
4.4.1 Patient Samples
[0791] Peripheral blood from GBM and aneurysm patients were collected from the Northwestern Central Nervous System Tissue Bank (NSTB). Plasma samples were stored at −80° C. until batch analysis. Peripheral blood mononuclear cells (PBMCs) were isolated using Ficoll-Paque (GE Healthcare) density gradient separation and stored in liquid nitrogen prior to initiating co-culture experiments. Snap-frozen tissue from surgically-resected GBM were collected from the NSTB. All tumors were diagnosed according to WHO diagnostic criteria by Dr. Craig Horbinski, M.D./Ph.D. Detailed information for patient tissue samples used in this study is shown in
4.4.2 The Cancer Genome Atlas (TCGA) Sample Description
[0792] The TCGA data for all cancer types analyzed in the current study were accessed from the UCSC Xena browser (http://xena.ucsc.edu/). RNA expression data assayed by RNASeq (Illumina Hi-seq platform) includes RSEM normalized level 3 data that is present in the TCGA as of Apr. 13, 2017. DNA methylation data were extracted from the same TCGA dataset. TCGA GBM gene expression data by AffyU133a array analysis were acquired from the UCSC Xena browser.
4.4.3 Glioblastoma Cell Lines and Patient-Derived GBM Xenografts (PDXs)
[0793] The human malignant glioma cell line U87 stably expressing luciferase (U87), the human IDO-overexpressing U87 cells (IDO-OE U87), and the mouse IDO.sup.−/−tGBM cell line were created and maintained as previously described (11, 22, 23). To generate the mIDO-overexpressing tGBM cell lines, a lentiviral vector that expresses mIDO-mGFP fusion protein was purchased from Origene (catalog #CW303099). To obtain lentiviral vector encoding enzyme-null mIDO, site mutagenesis of His.sup.350 into Ala was performed on the wild-type mIDO-mGFP lentiviral vector using QuickChange II Site-directed Mutagenesis kit (Agilent Technologies, catalog #200523) following the product protocol. Mutagenic primers were designed by the online QuickChange Primer Design Program (www.agilent.com/genomics/qcpd) and sequence information is shown in
[0794] IDO-deficient U87 cells (IDO-KO U87) were generated by the Applied StemCell Inc. using CRISPR-CAS9 technique. Briefly, human IDO guide RNAs targeting the exon 8 of human IDO gene were designed at CRISPR design web tool (Deskgene and CRISPOR) with at least three mismatches for NGG PAM sites. The crRNA-tracrRNA duplex were prepared by mixing equimolar concentration of Alt-R crRNA, Alt-R tracrRNA and ATTO 550 (catalog #1075298; Integrated DNA Technologies) followed by heating at 95° C. for 5 min and slowly cooled to room temperature. To prepare the Cas9/RNP complex, the crRNA-tracrRNA duplex and Alt-R S.p Cas9 nuclease V3 (catalog #1081059; Integrated DNA Technologies) were gently mixed and incubated at room temperature for 20 min. U87 cells were resuspended in SE nucleofection buffer (SE cell Line 4D-Nucleofector X kit L; V4XC-1024, Lonza) and incubated with Cas9/RNP complex at room temperature for 2 min and electroporated using a 4D nucleofector (4D-Nucleofector Core Unit: AAF-1002B; Lonza, 4D-Nucleofector X Unit: AAF-1002X, Lonza). 48 hours after transfection, cells were trypsinized and resuspended in phosphate-buffered saline (PBS) having 1% fetal bovine serum (FBS) and sorted by FACS based on ATTO signal intensity. After 7-14 days culture or formation of visible cell clones, genomic DNA were extract and subject to PCR. The PCR products were then Sanger-sequenced to identify clones that would result in frameshift mutation. IDO knockout at both mRNA and protein levels were confirmed by analyzing parental and IDO-KO U87 cells using RT-PCR and Western blotting, respectively.
[0795] The glioma cells from patient-derived GBM xenografts (PDX) were provided by the laboratory of Dr. C. David James at the Northwestern University and prepared as previously reported (24, 25). Except for the PDXs-derived human GBM cells, all the other cell lines used in this study were tested for mycoplasma prior to analysis and cultured in the DMEM/F12 medium (ThermoFisher Scientific, catalog #11320) supplemented with 10% FBS and 100 units/ml penicillin as well as 100 ug/ml streptomycin under 5% CO2 incubation condition unless described for specific experiments.
4.4.4 Animal and Tissue Preparation
[0796] Humanized mice reconstituted with human immune cells (NSG-SGM3-BLT), NOD.CB17-Prkdc.sup.scid/J (NOD-scid) mice, CrTac:NCr-Foxn1.sup.nu mice were used as previously described (11). Cre.sup.−/−IDO.sup.−/−tGBM mice were previously generated (21) by crossing transgenic mice that spontaneously develop glioblastoma after intraperitoneal injections of tamoxifen (26) with B6.129-Ido1.sup.tm1Alm/J (Jackson Laboratories). Mice were maintained under specific pathogen-free conditions in the Northwestern University Center for Comparative Medicine. For T cell depletion experiments, 200 μg anti-mouse CD4 (clone YTS191; BioXCell), 200 μg anti-mouse CD8 (clone YTS169.4; BioXCell) and 200 μg anti-mouse NK1.1 (clone PK136; BioXCell) were administered by intraperitoneal (i.p.) injection 3 days prior to and every 3 days after tumor cell engraftment up to 30 days after intracranial injection or at the declared experimental endpoints. Rat IgG2b (clone LTF-2, BioXCell) and mouse IgG2a (clone C1.18.4, BioXCell) were administrated at the same concentration and dosing schedule as for the leukocyte-depleting antibodies. For orthotopic brain tumor mouse modeling, 3×10.sup.5 tGBM or patient-derived xenograft (PDX) cells were intracranially-engrafted similar to previous studies (27). PDX tumor tissue was kindly provided by Dr. C. David James at the Northwestern University, from continuously propagated patient-resected GBM that was subcutaneously engrafted into nude mice. Mice were euthanized at the indicated time point(s). Brain tumor and non-tumor contralateral brain hemisphere tissue was collected, dissected, and washed in ice-cold phosphate-buffered saline (PBS), frozen in liquid nitrogen, and stored at −80° C. until analysis or processed for other techniques. Procedures for all mouse experiments were reviewed and approved by the Institutional Animal Care and Use Committee at Northwestern University and were in compliance with national and institutional guidelines.
4.4.5 Co-Culture Assays
[0797] For the tGBM cell-splenic monocyte co-culture, monocytes were isolated and enriched from mouse spleens using EasySep™ Mouse CD11b Positive Selection Kit (Catalog #18970, STEMCELL) according to the product protocol. Viability of the isolated cells was typically >90% as seen by trypan blue staining. CD11 b.sup.+ cells were seeded onto 12-well plate at a density of ˜1.5×10.sup.6 per well and cultured in RPMI-1640 medium supplemented with 10% heat-inactivated FBS, 100 mg/ml streptomycin, 100 U/ml penicillin, 10 ng/ml mouse recombinant IL-2 (R&D System, catalog #402-ML-020) over night. The next day non-attached cells were removed and adherent cells were washed once with PBS and incubated in fresh RPMI-1640 medium as described above for another 5 days. After counting the macrophages, tGBM cells were seeded on a 0.4 μm Transwell insert at 1:1 ratio and placed into the 12-well plate for co-culture of 48 hours. At the end of co-culture, tGBM cells and some macrophage cells were lysed using RNA Lysis Buffer from the PureLink RNA Mini Kit (Thermo Fisher Scientific, catalog #12183020) and stored at −80° C. for RT-PCR. The remaining macrophages were washed with PBS containing 5 mM EDTA and gently de-attached by cell scrappers followed by twice washing with PBS containing 2% FBS, then subject to flow cytometry analysis. Conditioned media from the co-culture were collected and filtered through a 40-um cell strainer and stored at −80° C. for HPLC analysis. The co-culture of U87 cells with patient PBMCs-derived T cells was performed as described in our previous study (11).
4.4.6 Hematoxylin and Eosin (H&E) Staining and Immunohistochemistry (IHC)
[0798] Brain tumors were dissected and fixed in 10% (w/v) neutral buffered formalin for 24˜72 hours. Formalin-fixed tissues were processed into paraffin blocks and sectioned at a thickness of 4 um. After deparafinization, antigen retrieval was performed using sodium citrate pH6 buffer. The slides were incubated in decloaking chamber (Biocare Medical) at 110° C. for 5 minutes; rinsed in distilled water 2 times and in 1×phosphate buffered saline (PBS) for 5 minutes, then incubated with anti-mGFP antibody (Origene, catalog #TA150122) (1:5000 dilution) in antibody diluent, overnight at 4° C. After rinsing with Tris-Buffered NaCl Solution with 0.1% Tween 20 (TBST), sections were further incubated with HRP-labelled anti-rabbit secondary antibody (BioCare Mach2 #RHRP520MM) for 1 hour. Slides were then washed for 3 minutes. Immunohistochemical reactions were visualized using a DAB substrate (DAKO). Tissue sections were counterstained with hematoxylin Gill II (Surgipath), mounted in the xylene based mounting medium, and visualized under a light microscope. Both H&E and IHC images were taken using a CRI Nuance camera on Zeiss Axioskop microscope at the Northwestern University Center for Advanced Microscopy Core. Histology services were provided by the Northwestern University Research Histology and Phenotyping Laboratory supported by NCI P30-CA060553.
4.4.7 Microarray Analysis
[0799] The microarray analysis was carried out at the Northwestern University NUSeq Core Facility using the human transcriptome analysis system, Clariom™ D Assay (Thermo Fisher Scientific). Briefly, 1×10.sup.5 cells per well of U87 cells or IDO-OE U87 cells were seeded on 12-well plate. After attachment, cells were transfected with human IDO-specific siRNA at a final concentration of 20 nM (GE Health Dharmacon) using either Lipofectamine RNAiMAX Transfection Reagent (Thermo Fisher Scientific, catalog #13778030) or jetPRIME siRNA transfection reagent (Polyplus-transfection). The sequences of hIDO siRNA duplex are shown in
[0800] The Affymetrix Transcriptome Analysis Console (TAC Version 4.0.2, Thermo Fisher Scientific) was used for normalization, summarization, and quality control of the resulting microarray data using the signal space transformation-robust multi-array average (SST-RMA) algorithm. Analysis of variance (ANOVA) empirical Bayes (eBayes) method using adjusted statistical p-values (p<0.05; fold change±2), was used for determination of the differentially expressed genes within the TAC console. The eBayes method which is suitable for small sample sizes, uses moderated t-statistics, where instead of the global or single gene estimated variances, a weighted average of the global and single-gene variances is used (28). 65 genes were identified as the most differentially expressed genes by IDO siRNA treatment between U87 cells and IDO-OE U87 cells (
4.4.8 Western Blotting
[0801] For cultured cell samples, media were removed, and cells were lysed in ice-cold RIPA buffer supplemented with 1× Halt protease/phosphatase inhibitor cocktail (Thermo Fisher Scientific). For GBM tissue samples, ˜50 mg tissue sample was homogenized in the above protein lysis buffer using the gentleMACS Dissociator (Miltenyi Biotec) following product protocol. The protein lysate was centrifuged at 12,600×g for 15 min, the supernatant was stored at −80° C. for further analysis. Protein concentration was measured by the bicinchoninic acid assay (Thermo Fisher Scientific). Equal amounts of protein were loaded in pre-cast Mini-PROTEAN TGX Stain-Free gels (Bio-Rad). After electrophoresis, protein was transferred the PVDF membrane followed by blocking in 5% (w/v) non-fat milk in 1×TBST for one hour, then probed with primary antibodies: anti-mGFP antibody (Origene, catalog #TA150122) (1:1000 dilution), anti-hIDO (Cell Signaling Technology, clone: D5J4E) (1:1000 dilution), anti-FH/FHL-1 antibody (Origene, clone: OTI5H5, catalog #TA804532) (1:1000 dilution), anti-GAPDH (Cell Signaling Technology, clone: 14C10) (1:1000 dilution) overnight at 4° C. After 5 times washing with 1×TBST, membrane was incubated with donkey anti-rabbit/goat IgG antibodies conjugated with horseradish peroxidase (Jackson ImmunoResearch Inc.). The blotting membrane was then incubated with SuperSignal West Pico/Femto ECL substrate (Thermo Fisher Scientific) and visualized on ChemiDoc (BioRad).
4.4.9 Flow Cytometry
[0802] Flow cytometry was performed as previously described (27). All the conjugated antibodies were purchased from eBioscience and detailed information is shown in
4.4.10 RNA Isolation and Real-Time RT-PCR
[0803] Total RNA was extracted from freshly dissected tissue samples and cultured cells using the Trizol Reagent and PureLink RNA Mini Kit (Thermo Fisher Scientific), respectively. 1 μg of total RNA was reverse transcribed into mRNA using iScript cDNA Synthesis Kit (Bio-Rad). Quantitative real-time PCR was performed on a CFX96 Touch Real-Time PCR Detection System using the default program setting (Bio-Rad). The sequences for all PCR primers are listed in
4.4.11 Trp and Kyn Analysis by High Performance Liquid Chromatography (HPLC)
[0804] Procedures for HPLC sample processing and analysis have been previously described (30).
4.4.12 Mass Spectrometry Quantification of CFH and FHL-1
[0805] Evaluation of plasma levels for CFH and FHL-1 has been described previously (31). Briefly, plasma samples were thawed and vortexed, and a 5 μl aliquot taken and diluted with 90 μl 50 mM ammonium bicarbonate, 2 μl of 1% (w/v) ProteaseMax (Promega, Southampton, UK) and 1 μl 500 mM dithiothreitol. This was incubated at 56° C. for 25 min to reduce cysteine residues. 3 μl 500 mM iodoacetamide was then added and sample incubated in the dark for a further 15 min. To digest the protein, a further 43 μl of 50 mM ammonium bicarbonate and 1 μl ProteaseMAX solution was added alongside 5 μl of 1 μg/μl endoproteinase Glu-C(Roche, Mannheim, Germany). Sample was mixed and digested for 16 hours at 25° C. Digested samples were spiked with heavy-labelled synthetic peptide standards (FH: VTYKCFE; FHL-1: NGWSPTPRCIRVSFTL, each containing S-carboxymethylated cysteine and heavy labelled amino acids at the underlined residues) (Cambridge Research Biochemicals, Cambridge, UK) to a final concentration of 47.6 μg/μl for the FH and 0.95 μg/μl for FHL-1. Peptides were dried in a centrifugal evaporator and resuspended in 50 μl 0.1% (v/v) trifluroacetic acid. 4 μL of this peptide solution was analysed—providing final on-column standard peptides loads of 200 fmol FH and 2 fmol FHL-1 peptides, respectively. Peptides were separated using an Agilent 1200 series liquid chromatography system with a C18 column (250 mm×2.1 mm I.D., Thermo Scientific Acclaim 120, 3 μm particle size) at 50° C. Peptides were eluted using a gradient elution increasing from 5% acetonitrile to 25%. The flow rate was maintained at 250 μL/min with an initial composition of 5% Buffer B (acetonitrile with 0.1% (v/v) formic acid). The following gradient elution profile was used to separate the peptides (time: % acetonitrile): 0 min: 5%; 2 min: 5%; 3 min: 12%; 12 min: 15%; 15 min: 20%; 30 min: 25%; 31 min: 90%; 39 min: 90%; 40 min: 5%; 49 min: 5%. Eluted peptides were detected using an Agilent 6595 triple quadrupole mass spectrometer in SRM mode monitoring three transitions per peptide as shown in
4.4.13 Cell Proliferation Assay
[0806] 2000-3000 tGBM cells per well were seeded on 96-well plate. Cell growth at different time points were measured using the Cell Counting Kit 8 (abcam, catalog #ab228554) following the product protocol. Absorbance at 460 nm was measured using a Synergy™ 2 multi-mode microplate reader (BioTek).
4.4.14 Statistical Analysis
[0807] The cutoff value for gene expression levels were determined with Cutoff Finder software (http://molpath.charite.de/cutoff/) using significance as the cutoff optimization method (32). Kaplan-Meier (KM) survival analysis was performed to estimate the survival distribution, while the Bonferroni-corrected, Mantel-Cox, or Gehan-Breslow-Wilcoxon log-rank tests were used to assess the statistical significance of differences between the stratified survival groups using GraphPad Prism (version 9, GraphPad Software, Inc., La Jolla, CA). Renyi family of test statistics was computed via SAS software (version9.4, SAS Institute Inc., Cary, NC) to determine the survival difference between two groups given the presence of crossing hazard rates. Pearson's correlation was used to analyze the relationship between each two genes' mRNA expression level.
[0808] Canonical-correlation analysis (CCA) was performed using concoro function in R package CCR. F-approximations of Wilks' Lambda was used to test the statistical significance of canonical correlation coefficients, using p.asym( ) function in R package CCP. Comparisons between multiple groups were analyzed by One-way ANOVA using GraphPad Prism software. Differences were considered to be statistically significant when P<0.05. Standard error of the mean (SEM) is presented as the error bar in all bar graphs and mean±SEM was utilized to describe the data throughout the text unless specifically noted.
4.5 Results
4.5.1 Tumor Cell IDO Increases Immune Suppression Through Non-Enzyme Activity
[0809] To determine if GBM cell IDO possesses non-enzyme activity, we bred B6.129-Ido1.sup.tm1Alm/J (Ido.sup.−/−) mice with GFAP(ERT.sup.2).fwdarw.Cre; p53.sup.fl/fl; Rb.sup.fl/fl; pTEN.sup.fl/fl mice (26) to generate an IDO-deficient tamoxifen-inducible transgenic mouse model of GBM (IDO.sup.−/−tGBM;
[0810] The in vivo role of Vector.sup.EMPTY-, IDO.sup.WT-, and IDO.sup.H350A-expressing IDO.sup.−/−tGBM cells was next characterised, after their intracranial injection into syngeneic IDO.sup.−/−tGBM mice (
4.5.2 IDO Enhances Complement Factor H Expression in Human GBM Cells
[0811] Since
4.5.3 IDO and CFH Demonstrate Similar Patterns of Expression in Patient-Resected GBM and Correlate with Glioma Patient Survival
[0812] Based on the similar patterns of IDO and CFH expression in the established human U87 GBM cell line (
4.5.4 IDO Enhances CFH Isoform Expression
[0813] The human CFH gene locus is on chromosome 1q32 in the regulators of complement activation (RCA) gene cluster. CFH encodes for an ˜155 kDa secreted glycoprotein comprised of 20 contiguous complement control protein (CCP) modules (
[0814] Protein expression for CFH and FHL-1 is also expressed in cell culture supernatants but not in intracellular U87 GBM cell lysate and is higher after treatment with IFNΓ (
4.5.5 Tumor Cell CFH Isoform Expression Enhances Intratumoral Immune Suppression and Decreases Survival in a Syngeneic Brain Tumor Model
[0815] To better understand the downstream effects of IDO-enhanced tumor cell CFH expression, IDO.sup.−/−tGBM cells were engineered to express the truncated CFH splice variant, FHL-1 cDNA (
4.5.6 Circulating and Intratumoral CFH Correlations in Patients with GBM
[0816] Since the two CFH isoforms are normally found in human plasma (35), the inventors next compared the protein levels for the full length and truncated CFH variants in non-tumor aneurysm- and age-matched GBM-patient plasma.
4.6 Discussion
[0817] The relationship between IDO and its regulatory effects on the complement cascade was initially described in the anatomical setting of placenta (36). At the time, there was no description of how treatment with the IDO pathway inhibitor, 1-methyl tryptophan (1-MT), affected intra-placental CFH expression levels or tryptophan and kynurenine levels. In a subsequent study, Li et al. demonstrated that pharmacologic IDO pathway modulation with either 1-MT or NLG919 triggered chemo-radiation-dependent complement C3 deposition at sites of tumor growth in the GL261-based mouse orthotopic brain tumor model (37). However, there was no description of how 1-MT or NLG919 affected intratumoral CFH expression levels or tryptophan and kynurenine levels. This is of significant notability since D1-MT, which has the most potent anti-brain tumor effects (17) and is used as the exclusive stereoisomer of 1-MT in clinical trials (15), does not effectively inhibit tryptophan metabolism (38, 39).
[0818] Complement C3 functions as a pivotal inducer by activating the complement-mediated inflammatory pathways, while CFH/FHL-1 plays a critical inhibitory role that suppresses complement-mediated inflammatory responses. With respect to the observations of our study, it's possible that the mechanistic effects of IDO enzyme activity on C3 activation are independent from those underlying the IDO non-enzyme effects on CFH/FHL-1 regulation. Since IDO protein is expressed in a majority of human cancers including GBM (13), further investigation that focuses on the molecular mechanism(s) underlying IDO regulation of C3 activation and CFH/FHL-1 is warranted. The present study, shows for the first time that human tumor cells utilize IDO non-enzyme activity to enhance the expression level of immunosuppressive CFH and its truncated isoform, FHL-1. It is further demonstrated that tumor cell FHL-1: (i) enhanced macrophage maturity, (ii) enhanced macrophage expression for ARG1, CCL2, and IL-6, and (iii) decreased the survival of mice with brain tumors in-part by suppressing the anti-GBM T and NK cell immune response. Translationally-relevant, it is also shown that IDO and CFH expression are positively correlated in patient-resected GBM and that increased intratumoral CFH/FHL-1 levels are associated with decreased GBM patient survival. This study therefore contributes a mechanistic understanding for why pharmacologic IDO enzyme inhibitor treatment fails to reverse the immunosuppressive effects of IDO when administered as a monotherapy (15).
[0819] Questions regarding the immunosuppressive role of CFH/FHL-1 remain to be addressed in the setting of GBM. First, does full-length CFH play an identically immune tolerant role as the isoform, FHL-1? Previous work showed that CFH-treated monocyte-derived dendritic cells (MoDCs) had a tolerogenic state, such as the production of immunomodulatory mediators including IL-10 and TGF-β, a reduced expression for CCR7 and chemotactic migration, impaired CD4.sup.+ T cell alloproliferation, and an induction of CD4.sup.+CD127.sup.low/−CD25.sup.highFoxp3.sup.+ regulatory T cells (40). One future direction to investigate how CFH/FHL-1 regulates complement pathway activation in GBM. However, as demonstrated in
[0820] Microarray analysis discovered a similar pattern of regulation between IDO and CFH in human GBM, in vitro, and this effect was confirmed in patient-resected tumors, in vivo. It is further shown that both the full length CFH and truncated variant, FHL-1, suppress the immune response in GBM. Although both CFH and FHL-1 have been previously associated with mechanisms of immune evasion (41, 42), no previous investigation focused on the role of FHL-1 in tumor-induced immunosuppression. Interestingly, FHL-1 is not expressed by mice (43) which allowed us to ignore the potential for multi-species gene expression competition of similar protein product during our investigation of IDO.sup.−/−tGBM cells expressing human FHL-1 cDNA. In summary, the inventors have revealed a non-enzymic function of IDO in human tumor cells that non-metabolically increases immunosuppression and contributes to poorer survival outcomes.
4.7 References for Example 4
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Liau L M, Ashkan K, Tran D D, Campian J L, Trusheim J E, Cobbs C S, et al. First results on survival from a large Phase 3 clinical trial of an autologous dendritic cell vaccine in newly diagnosed glioblastoma. J Trans Med. 2018; 16:142. [0827] 7. Reardon D A, Brandes A A, Omuro A, Mulholland P, Lim M, Wick A, et al. Effect of Nivolumab vs Bevacizumab in Patients With Recurrent Glioblastoma: The CheckMate 143 Phase 3 Randomized Clinical Trial. JAMA Oncol. 2020; 6:1003-10. [0828] 8. Uyttenhove C, Pilotte L, Theate I, Stroobant V, Colau D, Parmentier N, et al. Evidence for a tumoral immune resistance mechanism based on tryptophan degradation by indoleamine 2,3-dioxygenase. Nat Med. 2003; 9:1269-74. [0829] 9. Shimizu T, Nomiyama S, Hirata F, Hayaishi O. Indoleamine 2,3-dioxygenase. Purification and some properties. J Bio Chem. 1978; 253:4700-6. [0830] 10. Wainwright D A, Balyasnikova I V, Chang A L, Ahmed A U, Moon K S, Auffinger B, et al. IDO expression in brain tumors increases the recruitment of regulatory T cells and negatively impacts survival. Clin Cancer Res. 2012; 18:6110-21. [0831] 11. Zhai L, Ladomersky E, Lauing K L, Wu M, Genet M, Gritsina G, et al. Infiltrating T cells increase IDO1 expression in glioblastoma and contribute to decreased patient survival. Clin Cancer Res. 2017; 23:11. [0832] 12. Zhai L, Ladomersky E, Lenzen A, Nguyen B, Patel R, Lauing K L, et al. IDO1 in cancer: a Gemini of immune checkpoints. Cell Mol Immunol. 2018; 15:447-57. [0833] 13. Uyttenhove C, Pilotte L, Theate I, Stroobant V, Colau D, Parmentier N, et al. Evidence for a tumoral immune resistance mechanism based on tryptophan degradation by indoleamine 2,3-dioxygenase. Nature Med. 2003; 9:1269-74. [0834] 14. Zhai L, Lauing K L, Chang A L, Dey M, Qian J, Cheng Y, et al. The role of IDO in brain tumor immunotherapy. J Neurooncol. 2015; 123:395-403. [0835] 15. Zhai L, Spranger S, Binder D C, Gritsina G, Lauing K L, Giles F J, et al. Molecular Pathways: Targeting IDO1 and Other Tryptophan Dioxygenases for Cancer Immunotherapy. Clin Cancer Res. 2015; 21:5427-33. [0836] 16. Muller A J, Manfredi M G, Zakharia Y, Prendergast G C. Inhibiting IDO pathways to treat cancer: lessons from the ECHO-301 trial and beyond. Semin Immunopath. 2019; 41:41-8. [0837] 17. Wainwright D A, Chang A L, Dey M, Balyasnikova I V, Kim C K, Tobias A, et al. Durable therapeutic efficacy utilizing combinatorial blockade against IDO, CTLA-4, and PD-L1 in mice with brain tumors. Clin Cancer Res. 2014; 20:5290-301. [0838] 18. Ladomersky E, Zhai L, Lenzen A, Lauing K L, Qian J, Scholtens D M, et al. IDO1 Inhibition synergizes with radiation and PD-1 blockade to durably increase survival against advanced glioblastoma. Clin Cancer Res. 2018; 24:2559-73. [0839] 19. Ladomersky E, Zhai L, Lauing K L, Bell A, Xu J, Kocherginsky M, et al. Advanced age increases immunosuppression in the brain and decreases immunotherapeutic efficacy in subjects with glioblastoma. Clin Cancer Res. 2020; 26:5232-45. [0840] 20. Zhai L, Bell A, Ladomersky E, Lauing K L, Bollu L, Sosman J A, et al. Immunosuppressive IDO in Cancer: Mechanisms of Action, Animal Models, and Targeting Strategies. Frontiers in Immunology. 2020; 11:1185. [0841] 21. Zhai L, Ladomersky E, Dostal C R, Lauing K L, Swoap K, Billingham L K, et al. Non-tumor cell IDO1 predominantly contributes to enzyme activity and response to CTLA-4/PD-L1 inhibition in mouse glioblastoma. Brain, Behav Immun. 2017; 62:24-9. [0842] 22. Hashizume R, Ozawa T, Dinca E B, Banerjee A, Prados M D, James C D, et al. A human brainstem glioma xenograft model enabled for bioluminescence imaging. J Neurooncol. 2010; 96:151-9. [0843] 23. Zhai L, Ladomersky E, Dostal C R, Lauing K L, Swoap K, Billingham L K, et al. Non-tumor cell IDO1 predominantly contributes to enzyme activity and response to CTLA-4/PD-L1 inhibition in mouse glioblastoma. Brain, Behav Immun. 2017; 62:6. [0844] 24. Giannini C, Sarkaria J N, Saito A, Uhm J H, Galanis E, Carlson B L, et al. Patient tumor EGFR and PDGFRA gene amplifications retained in an invasive intracranial xenograft model of glioblastoma multiforme. Neuro-Oncology. 2005; 7:164-76. [0845] 25. Sarkaria J N, Carlson B L, Schroeder M A, Grogan P, Brown P D, Giannini C, et al. Use of an orthotopic xenograft model for assessing the effect of epidermal growth factor receptor amplification on glioblastoma radiation response. Clin Cancer Res. 2006; 12:2264-71. [0846] 26. Chow L M, Endersby R, Zhu X, Rankin S, Qu C, Zhang J, et al. Cooperativity within and among Pten, p53, and Rb pathways induces high-grade astrocytoma in adult brain. Cancer Cell. 2011; 19:305-16. [0847] 27. Wainwright D A, Balyasnikova I V, Chang A L, Ahmed A U, Moon K-S, Auffinger B, et al. IDO Expression in Brain Tumors Increases the Recruitment of Regulatory T Cells and Negatively Impacts Survival. Clin Cancer Res. 2012; 18:6110-21. [0848] 28. Efron B, Tibshirani R. Empirical bayes methods and false discovery rates for microarrays. Genetic Epidemiology. 2002; 23:70-86. [0849] 29. Livak K J, Schmittgen T D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001; 25:402-8. [0850] 30. Zhai L, Dey M, Lauing K L, Gritsina G, Kaur R, Lukas R V, et al. The kynurenine to tryptophan ratio as a prognostic tool for glioblastoma patients enrolling in immunotherapy. J Clin Neurosci. 2015. [0851] 31. Cipriani V, Tierney A, Griffiths J R, Zuber V, Sergouniotis P I, Yates J R W, et al. Beyond factor H: The impact of genetic-risk variants for age-related macular degeneration on circulating factor-H-like 1 and factor-H-related protein concentrations. Am J Hum Genet. 2021; 108:1385-400. [0852] 32. Budczies J, Klauschen F, Sinn B V, Gyorffy B, Schmitt W D, Darb-Esfahani S, et al. Cutoff Finder: a comprehensive and straightforward Web application enabling rapid biomarker cutoff optimization. PloS one. 2012; 7:e51862. [0853] 33. Littlejohn T K, Takikawa O, Truscott R J W, Walker M J. Asp274 and His346 Are Essential for Heme Binding and Catalytic Function of Human Indoleamine 2,3-Dioxygenase. Journal of Biological Chemistry. 2003; 278:29525-31. [0854] 34. O'Rourke D M, Nasrallah M P, Desai A, Melenhorst J J, Mansfield K, Morrissette J J D, et al. A single dose of peripherally infused EGFRvIII-directed CAR T cells mediates antigen loss and induces adaptive resistance in patients with recurrent glioblastoma. Sci Transl Med. 2017; 9. [0855] 35. Parente R, Clark S J, Inforzato A, Day A J. Complement factor H in host defense and immune evasion. Cellular and Molecular Life Sciences. 2017; 74:1605-24. [0856] 36. Munn D H, Zhou M, Attwood J T, Bondarev I, Conway S J, Marshall B, et al. 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Example 5: Analysis of Complement Proteins in the Blood of COVID-19 Patients
[0864] In further experiments, the inventors investigated the levels of complement proteins CFH, FHL1, FHR1, FHR2, FHR3, FHR4 and FHR5 in samples of blood obtained from 200 COVID-19 patients having varying severity of disease, and in samples of blood obtained from healthy control subjects (not having COVID-19). Blood samples were obtained from subjects in April-July 2020 at the time of the first COVID test. Progression of infection and clinical severity were monitored, with patients subsequently falling into one of five groups: asymptomatic disease (A), mild disease (B), disease requiring hospitalization but not supplemental oxygen (C), disease requiring hospitalization and low flow supplemental oxygen (D), disease requiring assisted ventilation (E). Detection of FH, FHL1, FHR1, FHR2, FHR3, FHR4 and FHR5 in samples from each group was performed using mass spectrometry as described in Examples 1 and 2.
[0865] The results are shown in