PEPTIDES AND COMBINATION OF PEPTIDES OF NON-CANONICAL ORIGIN FOR USE IN IMMUNOTHERAPY AGAINST DIFFERENT TYPES OF CANCERS

Abstract

The present invention relates to peptides, proteins, nucleic acids and cells for use in immunotherapeutic methods. In particular, the present invention relates to the immunotherapy of cancer. The present invention furthermore relates to tumor-associated T-cell peptide epitopes, alone or in combination with other tumor-associated peptides that can for example serve as active pharmaceutical ingredients of vaccine compositions that stimulate anti-tumor immune responses, or to stimulate T cells ex vivo and transfer into patients. Peptides bound to molecules of the major histocompatibility complex (MHC), or peptides as such, can also be targets of antibodies, soluble T-cell receptors, and other binding molecules.

Claims

1. A peptide consisting of the amino acid sequence RLCPAAPSEK (SEQ ID NO: 84) in the form of a pharmaceutically acceptable salt.

2. The peptide of claim 1, wherein said peptide has the ability to bind to an MHC class-I molecule, and wherein said peptide, when bound to said MHC, is capable of being recognized by CD8 T cells.

3. The peptide of claim 1, wherein the pharmaceutically acceptable salt is chloride salt.

4. The peptide of claim 1, wherein the pharmaceutically acceptable salt is acetate salt.

5. A composition comprising the peptide of claim 1, wherein the composition comprises an adjuvant and a pharmaceutically acceptable carrier.

6. The composition of claim 5, wherein the peptide is in the form of a chloride salt.

7. The composition of claim 5, wherein the peptide is in the form of an acetate salt.

8. The composition of claim 5 wherein the adjuvant is selected from the group consisting of anti-CD40 antibody, imiquimod, resiquimod, GM-CSF, cyclophosphamide, sunitinib, bevacizumab, interferon-alpha, interferon-beta, CpG oligonucleotides and derivatives, poly-(I:C) and derivatives, RNA, sildenafil, particulate formulations with poly(lactide co-glycolide) (PLG), virosomes, interleukin (IL)-1, IL-2, IL-4, IL-7, IL-12, IL-13, IL-15, IL-21, and IL-23.

9. The composition of claim 8, wherein the adjuvant is IL-2.

10. The composition of claim 8, wherein the adjuvant is IL-7.

11. The composition of claim 8, wherein the adjuvant is IL-12.

12. The composition of claim 8, wherein the adjuvant is IL-15.

13. The composition of claim 8, wherein the adjuvant is IL-21.

14. A pegylated peptide consisting of the amino acid sequence of RLCPAAPSEK (SEQ ID NO: 84) or a pharmaceutically acceptable salt thereof.

15. The peptide of claim 14, wherein the pharmaceutically acceptable salt is chloride salt.

16. The peptide of claim 14, wherein the pharmaceutically acceptable salt is acetate salt.

17. A composition comprising the pegylated peptide of claim 14 or pharmaceutically acceptable salt thereof, and a pharmaceutically acceptable carrier.

18. The composition of claim 5, wherein the pharmaceutically acceptable carrier is selected from the group consisting of saline, Ringer's solution, dextrose solution, and sustained release preparation.

19. The peptide in the form of a pharmaceutically acceptable salt of claim 1, wherein said peptide is produced by solid phase peptide synthesis or produced by a yeast cell or bacterial cell expression system.

20. A composition comprising the peptide of claim 1, wherein the composition is a pharmaceutical composition and comprises water and a buffer.

Description

BRIEF DESCRIPTION OF THE FIGURES

[0338] FIGS. 1A through 1F show the over-presentation of various peptides in different cancer tissues (black dots). Upper part: Median MS signal intensities from technical replicate measurements are plotted as dots for single HLA-A*02 positive normal (grey dots, left part of figure) and tumor samples (black dots, right part of figure) on which the peptide was detected. Boxes display median, 25th and 75th percentile of normalized signal intensities, while whiskers extend to the lowest data point still within 1.5 interquartile range (IQR) of the lower quartile, and the highest data point still within 1.5 IQR of the upper quartile. Normal organs are ordered according to risk categories (blood cells, blood vessels, brain, liver, lung: high risk, grey dots; reproductive organs, breast, prostate: low risk, grey dots; all other organs: medium risk; grey dots). Lower part: The relative peptide detection frequency in every organ is shown as spine plot. Numbers below the panel indicate number of samples on which the peptide was detected out of the total number of samples analyzed for each organ (N=440 for normal samples, N=490 for tumor samples). If the peptide has been detected on a sample but could not be quantified for technical reasons, the sample is included in this representation of detection frequency, but no dot is shown in the upper part of the figure. Tissues (from left to right): Normal samples: blood cells; bloodvess (blood vessels); brain; heart; liver; lung; monocytes; T-cells; adipose (adipose tissue); adrenal gl (adrenal gland); bile duct; bladder; bone marrow; esoph (esophagus); eye; gall bl (gallbladder); head&neck; intest. la (large intestine); intest. sm (small intestine); kidney; lymph node; nerve cent (central nerve); nerve perith (peripheral nerve); pancreas; parathyr (parathyroid gland); perit (peritoneum); pituit (pituitary); pleura; skel. mus (skeletal muscle); skin; spinal cord; spleen; stomach; thyroid; trachea; ureter; breast; ovary; placenta; prostate; testis; thymus; uterus. Tumor samples: AML (acute myeloid leukemia); BRCA (breast cancer); CCC (cholangiocellular carcinoma); CLL (chronic lymphocytic leukemia); CRC (colorectal cancer); GBC (gallbladder cancer); GBM (glioblastoma); GC (gastric cancer); GEJC (gastro-esophageal junction cancer); HCC (hepatocellular carcinoma); HNSCC (head and neck squamous cell carcinoma); MEL (melanoma); NHL (non-Hodgkin lymphoma); NSCLCadeno (non-small cell lung cancer adenocarcinoma); NSCLCother (NSCLC samples that could not unambiguously be assigned to NSCLCadeno or NSCLCsquam); NSCLCsquam (squamous cell non-small cell lung cancer); OC (ovarian cancer); OSCAR (esophageal cancer); PACA (pancreatic cancer); PRCA (prostate cancer); RCC (renal cell carcinoma); SCLC (small cell lung cancer); UBC (urinary bladder carcinoma); UEC (uterine endometrial cancer). FIG. 1A) Peptide: KLLDFSTRI (SEQ ID NO.: 1), FIG. 1B) Peptide: ALLDVLVKL (SEQ ID NO.: 2), FIG. 1C) Peptide: FLLVPSPIWQL (SEQ ID NO.: 3), FIG. 1D) Peptide: LVWEVVESV (SEQ ID NO.: 5), FIG. 1E) Peptide: SLLDKLSGI (SEQ ID NO.: 10). FIG. 1F shows the over-presentation of various peptides in different cancer tissues (black dots). Upper part: Median MS signal intensities from technical replicate measurements are plotted as dots for single HLA-A*03 positive normal (grey dots, left part of figure) and tumor samples (black dots, right part of figure) on which the peptide was detected. Boxes display median, 25th and 75th percentile of normalized signal intensities, while whiskers extend to the lowest data point still within 1.5 interquartile range (IQR) of the lower quartile, and the highest data point still within 1.5 IQR of the upper quartile. Normal organs are ordered according to risk categories (blood cells, blood vessels, brain, liver, lung: high risk, grey dots; reproductive organs, breast, prostate: low risk, grey dots; all other organs: medium risk; grey dots). Lower part: The relative peptide detection frequency in every organ is shown as spine plot. Numbers below the panel indicate number of samples on which the peptide was detected out of the total number of samples analyzed for each organ (N=36 for normal samples, N=107 for tumor samples). If the peptide has been detected on a sample but could not be quantified for technical reasons, the sample is included in this representation of detection frequency, but no dot is shown in the upper part of the figure. Tissues (from left to right): Normal samples: blood cells; bloodvess (blood vessels); brain; heart; liver; lung; adrenal gl (adrenal gland); bladder; gall bl (gallbladder); intest. sm (small intestine); lymph node; pancreas; skin; spleen; trachea. Tumor samples: AML (acute myeloid leukemia); BRCA (breast cancer); CCC (cholangiocellular carcinoma); CLL (chronic lymphocytic leukemia); CRC (colorectal cancer); GBC (gallbladder cancer); GBM (glioblastoma); GC (gastric cancer); HCC (hepatocellular carcinoma); HNSCC (head and neck squamous cell carcinoma); MEL (melanoma); NHL (non-Hodgkin lymphoma); NSCLCadeno (non-small cell lung cancer adenocarcinoma); NSCLCother (NSCLC samples that could not unambiguously be assigned to NSCLCadeno or NSCLCsquam); NSCLCsquam (squamous cell non-small cell lung cancer); OC (ovarian cancer); OSCAR (esophageal cancer); PACA (pancreatic cancer); PRCA (prostate cancer); RCC (renal cell carcinoma); SCLC (small cell lung cancer); UBC (urinary bladder carcinoma); UEC (uterine endometrial cancer) FIG. 1F) Peptide: SLLGAATVEPPK (SEQ ID NO.: 81; A*03).

[0339] FIGS. 2A through 2G show exemplary expression profile of source genes of the present invention that are over-expressed in different cancer samples. Tumor (black dots) and normal (grey dots) samples are grouped according to organ of origin. Box-and-whisker plots represent median FPKM value, 25th and 75th percentile (box) plus whiskers that extend to the lowest data point still within 1.5 interquartile range (IQR) of the lower quartile and the highest data point still within 1.5 IQR of the upper quartile. Normal organs are ordered according to risk categories. FPKM: fragments per kilobase per million mapped reads. Tissues (from left to right): Normal samples: blood cells; bloodvess (blood vessels); brain; heart; liver; lung; adipose (adipose tissue); adrenal gl (adrenal gland); bile duct; bladder; bone marrow; esoph (esophagus); eye; gall bl (gallbladder); head&neck; intest. la (large intestine); intest. sm (small intestine); kidney; lymph node; nerve perith (peripheral nerve); pancreas; parathyr (parathyroid gland); perit (peritoneum); pituit (pituitary); pleura; skel. mus (skeletal muscle); skin; spleen; stomach; thyroid; trachea; ureter; breast; ovary; placenta; prostate; testis; thymus; uterus. Tumor samples: AML (acute myeloid leukemia); BRCA (breast cancer); CCC (cholangiocellular carcinoma); CLL (chronic lymphocytic leukemia); CRC (colorectal cancer); GBC (gallbladder cancer); GBM (glioblastoma); GC (gastric cancer); HCC (hepatocellular carcinoma); HNSCC (head and neck squamous cell carcinoma); MEL (melanoma); NHL (non-Hodgkin lymphoma); NSCLCadeno (non-small cell lung cancer adenocarcinoma); NSCLCother (NSCLC samples that could not unambiguously be assigned to NSCLCadeno or NSCLCsquam); NSCLCsquam (squamous cell non-small cell lung cancer); OC (ovarian cancer); OSCAR (esophageal cancer); PACA (pancreatic cancer); PRCA (prostate cancer); RCC (renal cell carcinoma); SCLC (small cell lung cancer); UBC (urinary bladder carcinoma); UEC (uterine endometrial cancer). FIG. 2A) Ensembl ID: ENST00000225964, Peptide: ALLDVLVKL (SEQ ID No.: 2), FIG. 2B) Ensembl ID: ENST00000374472, Peptide: SLLDKLSGI (SEQ ID No 10), FIG. 2C) Ensembl ID: ENST00000617924, Peptide: FASERPPSV (SEQ ID No.: 33), FIG. 2D) Ensembl ID: ENST00000603198, Peptide: YIYEDEVRL (SEQ ID No.: 39), FIG. 2E) Ensembl ID: ENST00000420453, Peptide: AIWSTILIA (SEQ ID No.: 43), FIG. 2F) Ensembl ID: ENST00000473984, Peptide: IAISQLTFV (SEQ ID No.: 65), FIG. 2G) Ensembl ID ENS T00000375105.7, Peptide: LLLALRLSL (SEQ ID No.: 64).

[0340] FIGS. 3A and 3B show exemplary results of peptide-specific in vitro CD8+ T cell responses of a healthy HLA-A*02+ donor. CD8+ T cells were primed using artificial APCs coated with anti-CD28 mAb and HLA-A*02 in complex with SeqID No 102 peptide (GLDPTQFRV, Peptide Code: POLA1-003) (FIG. 3A, left panel) and SeqID No 103 peptide (SLVSYLDKV, Peptide Code: KRT16P-001) (FIG. 3B, left panel). After three cycles of stimulation, the detection of peptide-reactive cells was performed by 2D multimer staining with A*02/SeqID No 102 (FIG. 3A) and A*02/SeqID No 103 (FIG. 3B). Right panel (FIGS. 3A and 3B) show control staining of cells stimulated with irrelevant A*02/peptide complexes. Viable singlet cells were gated for CD8+ lymphocytes. Boolean gates helped excluding false-positive events detected with multimers specific for different peptides. Frequencies of specific multimer+ cells among CD8+ lymphocytes are indicated.

[0341] FIGS. 4A-4E show exemplary results of peptide-specific in vitro CD8+ T cell responses of a healthy HLA-A*02+ donor. CD8+ T cells were primed using artificial APCs coated with anti-CD28 mAb and HLA-A*02 in complex with SeqID No 18 peptide (KMMTFFQGL) (FIG. 4A, left panel), SeqID No 68 peptide (KLLADAFKV) (FIG. 4B, left panel), SeqID No 40 peptide (FTLPFLVNL) (FIG. 4C, left panel), SeqID No 19 peptide (MLLPWLPKL) (FIG. 4D, left panel) or SeqID No 48 peptide (MLAEIHPKA) (FIG. 4E, left panel), respectively. After three cycles of stimulation, the detection of peptide-reactive cells was performed by 2D multimer staining with A*02/SeqID No 18 (FIG. 4A), A*02/SeqID No 68 (FIG. 4B), A*02/SeqID No 40 (FIG. 4C), A*02/SeqID No 19 (FIG. 4D) or A*02/SeqID No 48 (FIG. 4E). Right panels (FIGS. 4A, 4B, 4C, 4D and 4E) show control staining of cells stimulated with irrelevant A*02/peptide complexes. Viable single cells were gated for CD8+ lymphocytes. Boolean gates helped excluding false-positive events detected with multimers specific for different peptides. Frequencies of specific multimer+ cells among CD8+ lymphocytes are indicated.

EXAMPLES

Example 1

[0342] Identification and Quantitation of Tumor Associated Peptides Presented on the Cell Surface

[0343] Tissue Samples

[0344] Patients' tumor tissues were obtained from: Asterand (Detroit, Mich., USA & Royston, Herts, UK); Bio-Options Inc. (Brea, Calif., USA); Geneticist Inc. (Glendale, Calif., USA); University Hospital Heidelberg (Heidelberg, Germany); ProteoGenex Inc. (Culver City, Calif., USA); Tissue Solutions Ltd (Glasgow, UK); University Hospital Munich (Munich, Germany). Normal tissues were obtained from Asterand (Detroit, Mich., USA & Royston, Herts, UK); Bio-Options Inc. (Brea, Calif., USA); BioServe (Beltsville, Md., USA); Capital BioScience Inc. (Rockville, Md., USA); Centre for Clinical Transfusion Medicine Tuebingen (Tubingen, Germany); Geneticist Inc. (Glendale, Calif., USA); Kyoto Prefectural University of Medicine (KPUM) (Kyoto, Japan); Osaka City University (OCU) (Osaka, Japan); ProteoGenex Inc. (Culver City, Calif., USA); Tissue Solutions Ltd (Glasgow, UK); University Hospital Geneva (Geneva, Switzerland); University Hospital Heidelberg (Heidelberg, Germany); University Hospital Tubingen (Tubingen, Germany); University Hospital Munich (Munich, Germany).

[0345] Written informed consents of all patients had been given before surgery or autopsy. Tissues were shock-frozen immediately after excision and stored until isolation of TUMAPs at −70° C. or below.

[0346] Isolation of HLA Peptides from Tissue Samples

[0347] HLA peptide pools from shock-frozen tissue samples were obtained by immune precipitation from solid tissues according to a slightly modified protocol (Falk et al., 1991; Seeger et al., 1999) using the HLA-A*02-specific antibody BB7.2, the HLA-A, —B, C-specific antibody W6/32, the HLA-DR specific antibody L243 and the HLA DP specific antibody B7/21, CNBr-activated sepharose, acid treatment, and ultrafiltration.

[0348] Mass Spectrometry Analyses

[0349] The HLA peptide pools as obtained were separated according to their hydrophobicity by reversed-phase chromatography (nanoAcquity UPLC system, Waters) and the eluting peptides were analyzed in LTQ-velos and fusion hybrid mass spectrometers (ThermoElectron) equipped with an ESI source. Peptide pools were loaded directly onto the analytical fused-silica micro-capillary column (75 μm i.d.×250 mm) packed with 1.7 μm C18 reversed-phase material (Waters) applying a flow rate of 400 nL per minute. Subsequently, the peptides were separated using a two-step 180 minute-binary gradient from 10% to 33% B at a flow rate of 300 nL per minute. The gradient was composed of Solvent A (0.1% formic acid in water) and solvent B (0.1% formic acid in acetonitrile). A gold coated glass capillary (PicoTip, New Objective) was used for introduction into the nanoESI source. The LTQ-Orbitrap mass spectrometers were operated in the data-dependent mode using a TOP5 strategy. In brief, a scan cycle was initiated with a full scan of high mass accuracy in the orbitrap (R=30 000), which was followed by MS/MS scans also in the orbitrap (R=7500) on the 5 most abundant precursor ions with dynamic exclusion of previously selected ions. Tandem mass spectra were interpreted by SEQUEST at a fixed false discovery rate (q<0.05) and additional manual control. In cases where the identified peptide sequence was uncertain it was additionally validated by comparison of the generated natural peptide fragmentation pattern with the fragmentation pattern of a synthetic sequence-identical reference peptide.

[0350] Label-free relative LC-MS quantitation was performed by ion counting i.e. by extraction and analysis of LC-MS features (Mueller et al., 2007). The method assumes that the peptide's LC-MS signal area correlates with its abundance in the sample. Extracted features were further processed by charge state deconvolution and retention time alignment (Mueller et al., 2008; Sturm et al., 2008). Finally, all LC-MS features were cross-referenced with the sequence identification results to combine quantitative data of different samples and tissues to peptide presentation profiles. The quantitative data were normalized in a two-tier fashion according to central tendency to account for variation within technical and biological replicates. Thus each identified peptide can be associated with quantitative data allowing relative quantification between samples and tissues. In addition, all quantitative data acquired for peptide candidates was inspected manually to assure data consistency and to verify the accuracy of the automated analysis. For each peptide a presentation profile was calculated showing the mean sample presentation as well as replicate variations. The profiles juxtapose acute myeloid leukemia, breast cancer, cholangiocellular carcinoma, chronic lymphocytic leukemia, colorectal cancer, gallbladder cancer, glioblastoma, gastric cancer, gastro-esophageal junction cancer, hepatocellular carcinoma, head and neck squamous cell carcinoma, melanoma, non-Hodgkin lymphoma, non-small cell lung cancer, ovarian cancer, esophageal cancer, pancreatic cancer, prostate cancer, renal cell carcinoma, small cell lung cancer, urinary bladder carcinoma, and uterine endometrial cancer samples to a baseline of normal tissue samples. Presentation profiles of exemplary over-presented peptides are shown in FIGS. 1A-1F. Peptide presentation on tumors for exemplary peptides are shown in Table 11.

[0351] Table 11 shows the presentation on various cancer entities for selected peptides, and thus the particular relevance of the peptides as mentioned for the diagnosis and/or treatment of the cancers as indicated (e.g. peptide SEQ ID No. 1 for acute myeloid leukemia, colorectal cancer, glioblastoma, gastric cancer, hepatocellular carcinoma, head and neck squamous cell carcinoma, melanoma, non-Hodgkin lymphoma, non-small cell lung cancer, ovarian cancer, esophageal cancer, prostate cancer, renal cell carcinoma, small cell lung cancer, urinary bladder carcinoma, uterine endometrial cancer, peptide SEQ ID No. 2 for breast cancer, colorectal cancer, gallbladder cancer, gastro-esophageal junction cancer, head and neck squamous cell carcinoma, melanoma, non-Hodgkin lymphoma, non-small cell lung cancer, ovarian cancer, esophageal cancer, pancreatic cancer, small cell lung cancer, uterine endometrial cancer).

TABLE-US-00011 TABLE 11 Overview of presentation of selected tumor-associated peptides of the present invention across entities. Cancer type: AML (acute myeloid leukemia); BRCA (breast cancer); CCC  (cholangiocellular carcinoma); CLL (chronic lymphocytic leukemia);  CRC (colorectal cancer); GBC (gallbladder cancer); GBM (glioblastoma); GC (gastric cancer); GEJC (gastro-esophageal junction cancer); HCC (hepatocellular carcinoma); HNSCC (head and neck squamous cell  carcinoma); MEL (melanoma); NHL (non-Hodgkin lymphoma); NSCLCadeno (non-small cell lung cancer adenocarcinoma); NSCLCother (NSCLC samples that could not unambiguously be assigned to NSCLCadeno or NSCLCsquam); NSCLCsquam (squamous cell non-small cell lung cancer); OC (ovarian cancer); OSCAR (esophageal cancer); PACA (pancreatic cancer); PRCA  (prostate cancer); RCC (renal cell carcinoma); SCLC (small cell lung cancer); UBC (urinary bladder carcinoma); UEC (uterine endometrial cancer) SEQ ID No. Sequence Peptide Presentation on cancer types   1 KLLDFSTRI AML, CRC, GBM, HCC, HNSCC, MEL, NHL, NSCLC, OC, OSCAR, PRCA, RCC, SCLC, UBC, UEC   2 ALLDVLVKL BRCA, CRC, GBC, GEJC, HNSCC, MEL, NHL, NSCLC, OC, OSCAR, PACA, SCLC, UEC   3 FLLVPSPIWQL AML, CLL, CRC, GBM, HCC, HNSCC, MEL, NHL, NSCLC, OC, RCC, SCLC, UEC   4 YLGDSHVLL AML, BRCA, CLL, CEC, GBM, HCC, MEL, NHL, NSCLC, OSCAR, RCC, SCLC, UBC   5 LVWEVVESV HCC, HNSCC, MEL, NHL, NSCLC, OC, OSCAR   6 ALHDSPVYL AML, BRCA, CCC, CRC, GBM, GC, HCC, HNSCC, MEL, NHL, NSCLC, OC, OSCAR, RCC, SCLC, UBC, UEC   7 ALWEEVKAT GBM, HCC, MEL, NSCLC, OC, SCLC, UEC SL   8 ILQSLVPAA CRC, NHL, NSCLC, OC, RCC   9 FLQEGDLISV CLL, CRC, NHL, NSCLC, OSCAR, SCLC  10 SLLDKLSGI CLL, CRC, NHL  11 ALLPHAPEAV BRCA, HCC, HNSCC, NHL, NSCLC, OC, OSCAR, SCLC, UBC  12 HLDSMNVSI AML, CLL, GC, MEL, NHL, PACA, PRCA  13 FLDEGSLLRL GC, HCC, HNSCC, MEL, OC, PACA, SCLC, UBC  14 LLIEVSEEL BRCA, CRC, GBM, HCC, OSCAR, MEL, NHL, NSCLC, PACA, SCLC  15 NLVMPLLHI AML, CLL, CRC, MEL, NSCLC, OC, PACA, UEC  16 ALLDAEQSPV AML, CLL, HCC, MEL, NHL, NSCLC, RCC AL  17 VLWDLRPSSL CLL, HNSCC,NHL, NSCLC, PACA, SCLC I  18 KMMTFFQGL HCC, NSCLC, NHL, OSCAR, PRCA, UBC  19 MLLPWLPKL CLL, GBM, HCC, HNSCC, NHL, NSCLC  20 VLISLPGKV HCC, MEL, NSCLC  21 FVFISPSFL AML, BRCA, CCC, CRC, GC, HCC, HNSCC, NHL, NSCLC, OC, PACA, PRCA  22 SLYDVPVGA CLL, CRC, GBM, HCC, MEL, NHL, NSCLC, OC, OSCAR, PACA, RCC, UBC  23 GLEVLDALL BRCA, CRC, GC, HCC, MEL, NHL, NSCLC, RCC, UEC  24 TLTSLNILL AML, CRC, GBM, HNSCC, MEL, NHL, NSCLC, OC, OSCAR, SCLC, UEC  25 ISVLNLSAI CCC, HCC, MEL, NHL, NSCLC, OC, PRCA, SCLC  26 KLWTSLVNL AML, CLL, CRC, GC, HNSCC, MEL, NSCLC, PACA, SCLC  27 IAAGVPNTDA BRCA, CLL, HCC, MEL, NSCLC, OC, RCC  28 SQLEKPETA HCC, HNSCC, NHL, NSCLC, SCLC, UEC  29 LLWEFPSMA AML, CLL, GBM, HNSCC, MEL, NHL, NSCLC, UEC  30 LLRLTLLPL CLL, HCC, NHL, NSCLC, OC, UEC  31 VVLPIVITL GC, HCC, NHL, NSCLC, RCC, PACA  32 VLSVSAVLGA CLL, GBM, GC, NSCLC, OC, OSCAR, PRCA, RCC  33 FASERPPSV BRCA, CRC, GC, GBC, GBM, HCC, HNSCC, MEL, NSCLC, OC, OSCAR, PACA, SCLC, UBC  34 LLNVEPAGA AML, BRCA, CLL, GBM, HCC, MEL, NHL, UEC  35 VLLNSNYPV NSCLC, PRCA, UBC  36 FQVTRTTGV GBC, HCC, NHL, NSCLC, RCC  37 KILDEFYNV CRC, GC, HCC, NSCLC  38 SLSAWLPSL GC, HCC, HNSCC, NSCLC, OC, OSCAR, RCC, UBC, UEC  39 YIYEDEVRL BRCA, CRC, HCC, HNSCC, NSCLC, OC, OSCAR, SCLC, UEC  40 FTLPFLVNL AML, CLL, CRC, GC, NHL, HCC, HNSCC, NSCLC, OC, UBC  41 LMASEGIWES CRC, GC, NSCLC, PRCA SL  42 WITPVIPAL AML, CLL, CRC, HCC, HNSCC, MEL, NHL, OC, PACA, RCC, SCLC, UBC, UEC  43 AIWSTILIA BRCA, CRC, NSCLC, OC, OSCAR, PRCA, SCLC  44 WLIPRQLAAA PRCA  45 ALYHQSPLL HNSCC, NSCLC, OSCAR, OC  46 AMVEIIPKV NSCLC, SCLC, UBC  47 ALLPGVPGL CRC, GBC, HNSCC, NSCLC, OC, RCC  48 MLAEIHPKA AML, BRCA, GBM, MEL, NSCLC  49 FLWDPRDVV GBM, OC L  50 GLASYLDRV BRCA, CRC, HCC, RCC, OC, OSCAR, SCLC, UBC  51 GLLTQVHIL AML, BRCA, CRC, GBM, HCC, NSCLC, PACA, UBC  52 LAFVSHVLI CRC, GC  53 TISISLSSV AML, CLL, CRC, GBM, GC, HCC, HNSCC, MEL, NHL, NSCLC, OC, OSCAR, PACA, PRCA, RCC, SCLC, UBC, UEC  54 GLSPDQVFL GBM, HNSCC, MEL, NHL  55 MVQQEKLFV AML, BRCA, CRC, GBM, GC, HCC, HNSCC, MEL, NSCLC, OSCAR, PACA, PRCA, RCC, SCLC, UBC, UEC  56 IITNLIVNI AML, CRC, GBC, GBM, HCC, HNSCC, MEL, NHL, NSCLC, OC, RCC, SCLC, UEC  57 YVLMTSLLL BRCA, CRC, GBM, GC, HCC, HNSCC, MEL, NSCLC, OSCAR, PRCA, SCLC  58 MIISHRALEL CLL, CRC, GBC, GBM, HCC, HNSCC, MEL, NSCLC, OC, PRCA, UBC  59 LAASTTFLGV HNSCC, NHL, NSCLC, OSCAR, PACA, UBC  60 LLLATLENL AML, CRC, GBM, MEL, NSCLC, SCLC, UBC, UEC  61 VLPWQPLLL AML, GC, HCC, HNSCC, NSCLC, OC, PACA  62 SLLGKPGLTI BRCA, CLL, CRC, GBC, HCC, NHL, NSCLC, OSCAR, RCC, PRCA, UBC, UEC  63 LSFKRSLSI AML, BRCA, CRC, GBM, HCC, NSCLC, PRCA, RCC, UBC  64 LLLALRLSL GBC, HCC, NHL, MEL, NSCLC, OSCAR, PACA  65 IAISQLTFV CLL, HCC, NHL, NSCLC, OSCAR, PRCA, SCLC, UEC  66 ILNELLNSI GBC, GC, HCC, MEL, NHL, PRCA, SCLC  67 ALKELMGPA NHL, NSCLC, RCC  68 KLLADAFKV AML, HCC, HNSCC, NSCLC, RCC, UBC, UEC  69 LLCPVVLQL AML, CLL, CRC, NSCLC, RCC, UBC, UEC  70 LLLQIEPAA GBM, HNSCC, NHL, NSCLC, UBC  71 WLMPVMPAL CLL, GBM, GC, MEL  72 YLSFIKILL MEL, PRCA  73 STTIINLIL AML, BRCA, CRC, HNSCC, HCC, NSCLC, OC, PACA  74 TLLSYSIPL CRC, GC, MEL, PACA, PRCA, UEC  75 TTQEAEKLLE BRCA, GBC, GC, HCC, HNSCC, NSCLC, OC, PACA, PRCA, R SCLC, UBC, UEC  76 TEQGPTGVTM AML, CLL, CRC, HCC, HNSCC, MEL, NSCLC, OSCAR, OC, RCC, UEC  77 VPAGVDVITE PRCA Y  78 GLLPPVRAM GBC, NHL, OSCAR  79 KIQDPGTAF PRCA  80 RDQIVTVSV AML, BRCA, NHL, SCLC, UBC, UEC  81 SLLGAATVEP AML, BRCA, CC, GBC, GBM, HCC, HNSCC, MEL, NHL, PK NSCLC, OC, OSCAR, PACA, PRCA, RCC, SCLC, UBC, UEC  82 LAPQMIIAL CLL, GBC, GC, HCC, MEL, NHL, NSCLC, OC, OSCAR, PRCA, UBC, SCLC  83 KPRGPTPL BRCA, GC, HCC, HNSCC, MEL, NSCLC, PACA, RCC, SCLC, UBC  84 RLCPAAPSEK BRCA, CCC, CRC, GBM, HCC, HNSCC, MEL, NHL, NSCLC, OC, OSCAR, PACA, RCC, UBC, UEC  85 VYLLTFPPL BRCA, GC,HCC, HNSCC, NHL, NSCLC, OC, OSCAR, UBC, UEC  86 LMIGKRIL HCC, HNSCC, NSCLC, OC, OSCAR, PACA, SCLC, UEC  87 LNLVSETEAM CRC, UEC VK  88 DEQETDAFLL NSCLC  89 MIFYVLQK AML, BRCA, CCC, CRC, GBM, HCC, HNSCC, MEL, NHL, NSCLC, OC, OSCAR, PACA, PRCA, RCC SCLC, UBC, UEC  90 YLRDFKIKR AML, BRCA, GBM, GC, HCC, HNSCC, NSCLC, PRCA, RCC, SCLC, UBC, UEC  91 SSHFILVTF CCC, GC, HCC, RCC  92 ELVAVTSVL CLL, NHL, PACA, SCLC, UEC  93 WQKNSMRL NSCLC  94 MGRRRNLY CCC, GBM, HNSCC, MEL, NHL, NSCLC, OC, OSCAR, PACA, PRCA, SCLC, UBC, UEC  95 QVKIVTLL GC, NSCLC, OC, PACA, PRCA, RCC  96 KIIEDLANTV CCC, CRC, HCC, NSCLC, OC, OSCAR, PRCA, SCLC, UBC, UEC  97 GLIDDKGTIK AML, BRCA, CRC, GBC, GBM, HCC, HNSCC, MEL, NHL, L NSCLC, OC, OSCAR, SCLC, UBC, UEC  98 SLMEVTHDL BRCA, GBM, HCC, HNSCC, NHL, NSCLC, OC, OSCAR, PRCA, UBC, UEC  99 ALMDGSESRF BRCA, CLL, HCC, HNSCC, MEL, NHL, NSCLC, OC, UEC FV 100 SLGPPPVGV AML, GBM, OC, UBC 101 KLPEGHLPEV HNSCC, MEL, NSCLC, OSCAR, PACA, RCC

Example 2

[0352] Expression Profiling of Genes Encoding the Peptides of the Invention

[0353] Over-presentation or specific presentation of a peptide on tumor cells compared to normal cells is sufficient for its usefulness in immunotherapy, and some peptides are tumor-specific despite their source protein occurring also in normal tissues. Still, mRNA expression profiling adds an additional level of safety in selection of peptide targets for immunotherapies. Especially for therapeutic options with high safety risks, such as affinity-matured TCRs, the ideal target peptide will be derived from a protein that is unique to the tumor and not found on normal tissues.

[0354] RNA Sources and Preparation

[0355] Surgically removed tissue specimens were provided as indicated above (see Example 1) after written informed consent had been obtained from each patient. Tumor tissue specimens were snap-frozen immediately after surgery and later homogenized with mortar and pestle under liquid nitrogen. Total RNA was prepared from these samples using TRI Reagent (Ambion, Darmstadt, Germany) followed by a cleanup with RNeasy (QIAGEN, Hilden, Germany); both methods were performed according to the manufacturer's protocol.

[0356] Total RNA from healthy human tissues for RNASeq experiments was obtained from: Asterand (Detroit, Mich., USA & Royston, Herts, UK); Bio-Options Inc. (Brea, Calif., USA); Geneticist Inc. (Glendale, Calif., USA); ProteoGenex Inc. (Culver City, Calif., USA); Tissue Solutions Ltd (Glasgow, UK).

[0357] Total RNA from tumor tissues for RNASeq experiments was obtained from: Asterand (Detroit, Mich., USA & Royston, Herts, UK); BioCat GmbH (Heidelberg, Germany); BioServe (Beltsville, Md., USA); Geneticist Inc. (Glendale, Calif., USA); Istituto Nazionale Tumori “Pascale” (Naples, Italy); ProteoGenex Inc. (Culver City, Calif., USA); University Hospital Heidelberg (Heidelberg, Germany).

[0358] Quality and quantity of all RNA samples were assessed on an Agilent 2100 Bioanalyzer (Agilent, Waldbronn, Germany) using the RNA 6000 Pico LabChip Kit (Agilent).

[0359] RNAseq Experiments

[0360] Gene expression analysis of—tumor and normal tissue RNA samples was performed by next generation sequencing (RNAseq) by CeGaT (Tubingen, Germany). Briefly, sequencing libraries are prepared using the Illumina HiSeq v4 reagent kit according to the provider's protocol (Illumina Inc., San Diego, Calif., USA), which includes RNA fragmentation, cDNA conversion and addition of sequencing adaptors. Libraries derived from multiple samples are mixed equimolar and sequenced on the Illumina HiSeq 2500 sequencer according to the manufacturer's instructions, generating 50 bp single end reads. Processed reads are mapped to the human genome (GRCh38) using the STAR software. Expression data are provided on transcript level as RPKM (Reads Per Kilobase per Million mapped reads, generated by the software Cufflinks) and on exon level (total reads, generated by the software Bedtools), based on annotations of the ensembl sequence database (Ensembl77). Exon reads are normalized for exon length and alignment size to obtain RPKM values.

[0361] Exemplary expression profiles of source genes of the present invention that are highly over-expressed or exclusively expressed in acute myeloid leukemia, breast cancer, cholangiocellular carcinoma, chronic lymphocytic leukemia, colorectal cancer, gallbladder cancer, glioblastoma, gastric cancer, gastro-esophageal junction cancer, hepatocellular carcinoma, head and neck squamous cell carcinoma, melanoma, non-Hodgkin lymphoma, non-small cell lung cancer, ovarian cancer, esophageal cancer, pancreatic cancer, prostate cancer, renal cell carcinoma, small cell lung cancer, urinary bladder carcinoma, and uterine endometrial cancer are shown in FIGS. 1A-1F. Expression scores for further exemplary genes are shown in Table 12.

[0362] Table 12: Expression scores. The table lists peptides from genes that are very highly over-expressed in tumors compared to a panel of normal tissues (+++), highly over-expressed in tumors compared to a panel of normal tissues (++) or over-expressed in tumors compared to a panel of normal tissues (+). The baseline for this score was calculated from measurements of the following relevant normal tissues: blood cells; blood vessels; brain; heart; liver; lung; adipose tissue; adrenal gland; bile duct; bladder; bone marrow; cartilage; esophagus; eye; gallbladder; head&neck; large intestine; small intestine; kidney; lymph node; central nerve; peripheral nerve; pancreas; parathyroid gland; peritoneum; pituitary; pleura; skeletal muscle; skin; spinal cord; spleen; stomach; thyroid; trachea; ureter.

[0363] In case expression data for several samples of the same tissue type were available, the arithmetic mean of all respective samples was used for the calculation.

TABLE-US-00012 SEQ ID Gene No Sequence Expression  3 FLLVPSPIWQL +  5 LVWEVVESV +  9 FLQEGDLISV + 10 SLLDKLSGI ++ 14 LLIEVSEEL ++ 17 VLWDLRPSSLI ++ 18 KMMTFFQGL + 19 MLLPWLPKL + 24 TLTSLNILL + 31 VVLPIVITL + 32 VLSVSAVLGA ++ 33 FASERPPSV +++ 34 LLNVEPAGA ++ 35 VLLNSNYPV +++ 36 FQVTRTTGV +++ 37 KILDEFYNV ++ 38 SLSAWLPSL +++ 39 YIYEDEVRL +++ 40 FTLPFLVNL ++ 41 LMASEGIWESSL ++ 42 WITPVIPAL + 43 AIWSTILIA ++++ 44 WLIPRQLAAA ++++ 46 AMVEIIPKV + 47 ALLPGVPGL ++ 48 MLAEIHPKA ++ 49 FLWDPRDVVL ++ 51 GLLTQVHIL ++ 52 LAFVSHVLI +++ 53 TISISLSSV ++ 54 GLSPDQVFL ++ 56 IITNLIVNI ++++ 57 YVLMTSLLL +++ 59 LAASTTFLGV ++ 60 LLLATLENL + 62 SLLGKPGLTI ++ 63 LSFKRSLSI ++ 64 LLLALRLSL +++ 65 IAISQLTFV ++++ 66 ILNELLNSI + 67 ALKELMGPA ++ 68 KLLADAFKV +++ 69 LLCPVVLQL +++ 70 LLLQIEPAA +++ 71 WLMPVMPAL ++

Example 3

[0364] In Vitro Immunogenicity for MHC Class I Presented Peptides

[0365] In order to obtain information regarding the immunogenicity of the TUMAPs of the present invention, the inventors performed investigations using an in vitro T-cell priming assay based on repeated stimulations of CD8+ T cells with artificial antigen presenting cells (aAPCs) loaded with peptide/MHC complexes and anti-CD28 antibody. This way the inventors could show immunogenicity for HLA-A*02:01 restricted TUMAPs of the invention, demonstrating that these peptides are T-cell epitopes against which CD8+ precursor T cells exist in humans (Table 13a and 13b).

[0366] In Vitro Priming of CD8+ T Cells

[0367] In order to perform in vitro stimulations by artificial antigen presenting cells loaded with peptide-MHC complex (pMHC) and anti-CD28 antibody, the inventors first isolated CD8+ T cells from fresh HLA-A*02 leukapheresis products via positive selection using CD8 microbeads (Miltenyi Biotec, Bergisch-Gladbach, Germany) of healthy donors obtained from the University clinics Mannheim, Germany, after informed consent.

[0368] PBMCs and isolated CD8+ lymphocytes were incubated in T-cell medium (TCM) until use consisting of RPMI-Glutamax (Invitrogen, Karlsruhe, Germany) supplemented with 10% heat inactivated human AB serum (PAN-Biotech, Aidenbach, Germany), 100 U/ml Penicillin/100 μg/ml Streptomycin (Cambrex, Cologne, Germany), 1 mM sodium pyruvate (CC Pro, Oberdorla, Germany), 20 μg/ml Gentamycin (Cambrex). 2.5 ng/ml IL-7 (PromoCell, Heidelberg, Germany) and 10 U/ml IL-2 (Novartis Pharma, Nurnberg, Germany) were also added to the TCM at this step.

[0369] Generation of pMHC/anti-CD28 coated beads, T-cell stimulations and readout was performed in a highly defined in vitro system using four different pMHC molecules per stimulation condition and 8 different pMHC molecules per readout condition.

[0370] The purified co-stimulatory mouse IgG2a anti human CD28 Ab 9.3 (Jung et al., 1987) was chemically biotinylated using Sulfo-N-hydroxysuccinimidobiotin as recommended by the manufacturer (Perbio, Bonn, Germany) Beads used were 5.6 μm diameter streptavidin coated polystyrene particles (Bangs Laboratories, Illinois, USA).

[0371] pMHC used for positive and negative control stimulations were A*0201/MLA-001 (peptide ELAGIGILTV (SEQ ID NO. 104) from modified Melan-A/MART-1) and A*0201/DDX5-001 (YLLPAIVHI from DDX5, SEQ ID NO. 105), respectively.

[0372] 800.000 beads/200 μl were coated in 96-well plates in the presence of 4×12.5 ng different biotin-pMHC, washed and 600 ng biotin anti-CD28 were added subsequently in a volume of 200 Stimulations were initiated in 96-well plates by co-incubating 1×10.sup.6 CD8+ T cells with 2×10.sup.5 washed coated beads in 200 μl TCM supplemented with 5 ng/ml IL-12 (PromoCell) for 3 days at 37° C. Half of the medium was then exchanged by fresh TCM supplemented with 80 U/ml IL-2 and incubating was continued for 4 days at 37° C. This stimulation cycle was performed for a total of three times. For the pMHC multimer readout using 8 different pMHC molecules per condition, a two-dimensional combinatorial coding approach was used as previously described (Andersen et al., 2012) with minor modifications encompassing coupling to 5 different fluorochromes. Finally, multimeric analyses were performed by staining the cells with Live/dead near IR dye (Invitrogen, Karlsruhe, Germany), CD8-FITC antibody clone SK1 (BD, Heidelberg, Germany) and fluorescent pMHC multimers. For analysis, a BD LSRII SORP cytometer equipped with appropriate lasers and filters was used. Peptide specific cells were calculated as percentage of total CD8+ cells. Evaluation of multimeric analysis was done using the FlowJo software (Tree Star, Oregon, USA). In vitro priming of specific multimer+CD8+ lymphocytes was detected by comparing to negative control stimulations. Immunogenicity for a given antigen was detected if at least one evaluable in vitro stimulated well of one healthy donor was found to contain a specific CD8+ T-cell line after in vitro stimulation (i.e. this well contained at least 1% of specific multimer+ among CD8+ T-cells and the percentage of specific multimer+ cells was at least 10× the median of the negative control stimulations).

[0373] In Vitro Immunogenicity for Acute Myeloid Leukemia, Breast Cancer, Cholangiocellular Carcinoma, Chronic Lymphocytic Leukemia, Colorectal Cancer, Gallbladder Cancer, Glioblastoma, Gastric Cancer, Gastro-Esophageal Junction Cancer, Hepatocellular Carcinoma, Head and Neck Squamous Cell Carcinoma, Melanoma, Non-Hodgkin Lymphoma, Non-Small Cell Lung Cancer, Ovarian Cancer, Esophageal Cancer, Pancreatic Cancer, Prostate Cancer, Renal Cell Carcinoma, Small Cell Lung Cancer, Urinary Bladder Carcinoma, and Uterine Endometrial Cancer Peptides

[0374] For tested HLA class I peptides, in vitro immunogenicity could be demonstrated by generation of peptide specific T-cell lines. Exemplary flow cytometry results after TUMAP-specific multimer staining for 7 peptides of the invention are shown in FIGS. 3A and 3B and FIG. 4A-4E together with corresponding negative controls. Results for 30 peptides from the invention are summarized in Table 13a and 13b.

TABLE-US-00013 TABLE 13a in vitro immunogenicity of HLA class I   peptides of the invention Exemplary results of in vitro immunogenicity  experiments conducted by the applicant for  the peptides of the invention. <20% = +;  20%-49% = ++; 50%-69% = +++; >=70% = ++++ SEQ ID No Sequence Wells positive [%] 102 GLDPTQFRV ++++ 103 SLVSYLDKV +

TABLE-US-00014 TABLE 13b in vitro immunogenicity of HLA class I  peptides of the invention Exemplary results of in vitro immunogenicity  experiments conducted by the applicant for  the peptides of the invention. <20% = +;  20-49% = ++; 50-69% = +++; ≥70% = ++++ SEQ ID No Sequence Wells positive [%]   1 KLLDFSTRI +   2 ALLDVLVKL +   3 FLLVPSPIWQL +   4 YLGDSHVLL +   6 ALHDSPVYL ++   7 ALWEEVKATSL +  13 FLDEGSLLRL +  18 KMMTFFQGL ++++  19 MLLPWLPKL +++  26 KLWTSLVNL +++  29 LLWEFPSMA ++  31 VVLPIVITL ++  33 FASERPPSV +++  36 FQVTRTTGV +  37 KILDEFYNV +++  38 SLSAWLPSL +  40 FTLPFLVNL +++  46 AMVEIIPKV +  47 ALLPGVPGL ++  48 MLAEIHPKA +++  49 FLWDPRDVVL +  50 GLASYLDRV +  51 GLLTQVHIL +  65 IAISQLTFV +  68 KLLADAFKV ++++  74 TLLSYSIPL +  96 KIIEDLANTV ++ 101 KLPEGHLPEV +

Example 4

[0375] Synthesis of Peptides

[0376] All peptides were synthesized using standard and well-established solid phase peptide synthesis using the Fmoc-strategy. Identity and purity of each individual peptide have been determined by mass spectrometry and analytical RP-HPLC. The peptides were obtained as white to off-white lyophilizes (trifluoro acetate salt) in purities of >50%. All TUMAPs are preferably administered as trifluoro-acetate salts or acetate salts, other salt-forms are also possible.

Example 5

[0377] MHC Binding Assays

[0378] Candidate peptides for T cell based therapies according to the present invention were further tested for their MHC binding capacity (affinity). Results for 79 peptides from the invention are summarized in Table 14.

[0379] The individual peptide-MHC complexes were produced by UV-ligand exchange, where a UV-sensitive peptide is cleaved upon UV-irradiation and exchanged with the peptide of interest as analyzed. Only peptide candidates that can effectively bind and stabilize the peptide-receptive MHC molecules prevent dissociation of the MHC complexes. To determine the yield of the exchange reaction, an ELISA was performed based on the detection of the light chain (β2m) of stabilized MHC complexes. The assay was performed as generally described in Rodenko et al. (Rodenko et al., 2006).

[0380] 96 well MAXISorp plates (NUNC) were coated over night with 2 μg/ml streptavidin in PBS at room temperature, washed 4× and blocked for 1 h at 37° C. in 2% BSA containing blocking buffer. Refolded HLA-A*02:01/MLA-001 monomers served as standards, covering the range of 15-500 ng/ml. Peptide-MHC monomers of the UV-exchange reaction were diluted 100 fold in blocking buffer. Samples were incubated for 1 h at 37° C., washed four times, incubated with 2 μg/ml HRP conjugated anti-β2m for 1 h at 37° C., washed again and detected with TMB solution that is stopped with NH.sub.2SO.sub.4. Absorption was measured at 450 nm. Candidate peptides that show a high exchange yield (preferably higher than 50%, most preferred higher than 75%) are generally preferred for a generation and production of antibodies or fragments thereof, and/or T cell receptors or fragments thereof, as they show sufficient avidity to the MHC molecules and prevent dissociation of the MHC complexes.

TABLE-US-00015 TABLE 14 MHC class I binding scores. Binding of  HLA-class I restricted peptides to HLA- A*02:01 was ranged by peptide exchange  yield: ≥10% = +; ≥20% = ++; ≥50 = +++;  ≥75% = ++++ SEQ ID No Sequence Peptide exchange   1 KLLDFSTRI ++++   2 ALLDVLVKL ++++   3 FLLVPSPIWQL ++++   4 YLGDSHVLL ++++   5 LVWEVVESV ++++   6 ALHDSPVYL ++++   7 ALWEEVKATSL ++++   8 ILQSLVPAA ++++   9 FLQEGDLISV ++++  10 SLLDKLSGI ++++  11 ALLPHAPEAV +++  12 HLDSMNVSI ++++  13 FLDEGSLLRL ++++  14 LLIEVSEEL ++++  15 NLVMPLLHI ++  16 ALLDAEQSPVAL ++++  17 VLWDLRPSSLI ++++  18 KMMTFFQGL ++++  19 MLLPWLPKL ++++  20 VLISLPGKV ++  21 FVFISPSFL +++  22 SLYDVPVGA ++++  23 GLEVLDALL ++  24 TLTSLNILL ++++  25 ISVLNLSAI ++  26 KLWTSLVNL ++++  27 IAAGVPNTDA ++  28 SQLEKPETA +++  29 LLWEFPSMA ++++  30 LLRLTLLPL ++  31 VVLPIVITL ++++  32 VLSVSAVLGA +++  33 FASERPPSV ++++  34 LLNVEPAGA ++++  35 VLLNSNYPV ++++  36 FQVTRTTGV ++++  37 KILDEFYNV ++++  38 SLSAWLPSL ++++  39 YIYEDEVRL ++++  40 FTLPFLVNL ++++  41 LMASEGIWESSL +++  42 WITPVIPAL ++++  43 AIWSTILIA ++  44 WLIPRQLAAA ++++  45 ALYHQSPLL ++++  46 AMVEIIPKV ++++  47 ALLPGVPGL ++++  48 MLAEIHPKA ++++  49 FLWDPRDVVL ++++  50 GLASYLDRV ++++  51 GLLTQVHIL ++++  52 LAFVSHVLI ++  53 TISISLSSV ++++  54 GLSPDQVFL ++++  55 MVQQEKLFV +++  56 IITNLIVNI +++  57 YVLMTSLLL ++++  58 MIISHRALEL ++  59 LAASTTFLGV ++++  60 LLLATLENL ++++  61 VLPWQPLLL ++  62 SLLGKPGLTI ++++  63 LSFKRSLSI ++  64 LLLALRLSL +  65 IAISQLTFV ++++  66 ILNELLNSI ++++  67 ALKELMGPA ++  68 KLLADAFKV ++++  69 LLCPVVLQL ++++  70 LLLQIEPAA ++++  71 WLMPVMPAL ++++  73 STTIINLIL ++  74 TLLSYSIPL ++++  96 KIIEDLANTV ++++  97 GLIDDKGTIKL ++++  98 SLMEVTHDL ++++  99 ALMDGSESRFFV ++++ 100 SLGPPPVGV ++++ 101 KLPEGHLPEV ++++

Example 6

[0381] Absolute Quantitation of Tumor Associated Peptides Presented on the Cell Surface

[0382] The generation of binders, such as antibodies and/or TCRs, is a laborious process, which may be conducted only for a number of selected targets. In the case of tumor-associated and—specific peptides, selection criteria include but are not restricted to exclusiveness of presentation and the density of peptide presented on the cell surface. In addition to the isolation and relative quantitation of peptides as described in EXAMPLE 1, the inventors did analyze absolute peptide copies per cell as described in WO 2016/107740. The quantitation of TUMAP copies per cell in solid tumor samples requires the absolute quantitation of the isolated TUMAP, the efficiency of the TUMAP isolation process, and the cell count of the tissue sample analyzed.

[0383] Peptide Quantitation by Nano LC-MS/MS

[0384] For an accurate quantitation of peptides by mass spectrometry, a calibration curve was generated for each individual peptide using two different isotope labeled peptide variants (one or two isotope-labeled amino acids are included during TUMAP synthesis). These isotopes labeled variants differ from the tumor-associated peptide only in their mass but show no difference in other physicochemical properties (Anderson et al., 2012). For the peptide calibration curve, a series of nano LC-MS/MS measurements was performed to determine the ration of MS/MS signals of titrated (singly isotope-labeled peptide) to constant (doubly isotope labeled peptide) isotope labeled peptides.

[0385] The doubly isotope labeled peptide, also called internal standard, was further spiked to each MS sample and all MS signals were normalized to the MS signal of the internal standard to level out potential technical variances between MS experiments.

[0386] The calibration curves were prepared in at least three different matrices, i.e. HLA peptide eluates from natural samples similar to the routine MS samples, and each preparation was measured in duplicate MS runs. For evaluation, MS signals were normalized to the signal of the internal standard and a calibration curve was calculated by logistic regression.

[0387] For the quantitation of tumor-associated peptides from tissue samples, the respective samples were also spiked with the internal standard; the MS signals were normalized to the internal standard and quantified using the peptide calibration curve.

[0388] Efficiency of Peptide/MHC Isolation

[0389] As for any protein purification process, the isolation of proteins from tissue samples is associated with a certain loss of the protein of interest. To determine the efficiency of TUMAP isolation, peptide/MHC complexes were generated for all TUMAPs selected for absolute quantitation. To be able to discriminate the spiked from the natural peptide/MHC complexes, single-isotope-labelled versions of the TUMAPs were used, i.e. one isotope-labelled amino acid was included in TUMAP synthesis. These complexes were spiked into the freshly prepared tissue lysates, i.e. at the earliest possible point of the TUMAP isolation procedure, and then captured like the natural peptide/MHC complexes in the following affinity purification. Measuring the recovery of the single-labelled TUMAPs therefore allows conclusions regarding the efficiency of isolation of individual natural TUMAPs.

[0390] The efficiency of isolation was analyzed in a small set of samples and was comparable among these tissue samples. In contrast, the isolation efficiency differs between individual peptides. This suggests that the isolation efficiency, although determined in only a limited number of tissue samples, may be extrapolated to any other tissue preparation. However, it is necessary to analyze each TUMAP individually as the isolation efficiency may not be extrapolated from one peptide to others.

[0391] Determination of the Cell Count in Solid, Frozen Tissue

[0392] In order to determine the cell count of the tissue samples subjected to absolute peptide quantitation, the inventors applied DNA content analysis. This method is applicable to a wide range of samples of different origin and, most importantly, frozen samples (Alcoser et al., 2011; Forsey and Chaudhuri, 2009; Silva et al., 2013). During the peptide isolation protocol, a tissue sample is processed to a homogenous lysate, from which a small lysate aliquot is taken. The aliquot is divided in three parts, from which DNA is isolated (QiaAmp DNA Mini Kit, Qiagen, Hilden, Germany). The total DNA content from each DNA isolation is quantified using a fluorescence-based DNA quantitation assay (Qubit dsDNA HS Assay Kit, Life Technologies, Darmstadt, Germany) in at least two replicates.

[0393] In order to calculate the cell number, a DNA standard curve from aliquots of isolated healthy blood cells from several donors, with a range of defined cell numbers, has been generated. The standard curve is used to calculate the total cell content from the total DNA content from each DNA isolation. The mean total cell count of the tissue sample used for peptide isolation is then extrapolated considering the known volume of the lysate aliquots and the total lysate volume.

[0394] Peptide Copies Per Cell

[0395] With data of the aforementioned experiments, the inventors calculated the number of TUMAP copies per cell by dividing the total peptide amount by the total cell count of the sample, followed by division through isolation efficiency. Copy cell number for selected peptides are shown in Table 15.

TABLE-US-00016 TABLE 15 Absolute copy numbers. The table lists the results of absolute peptide quantitation in tumor samples. The median number of copies per cell are indicated for each peptide: <25 = +; ≥25 = ++; ≥50 = +++; ≥75 = ++++. The number of samples, in which evaluable, high quality MS data are available, is indicated. SEQ ID Copies per Number of No. Peptide Code cell (median) samples 1 NUDCD2-001 +++ 8 2 COLPDG-001 ++++ 12 4 altORF-002 + 7 5 altORF-003 ++++ 13 6 altORF-004 + 23 7 altORF-005 + 1 8 altORF-006 ++++ 12 9 altORF-007 ++ 11 10 altORF-008 + 11 11 altORF-009 + 13 39 altORF-037 ++ 4 96 KRT18-001 ++ 1 97 CDC2-006 ++ 10 100 CIZ1-001 + 1

REFERENCE LIST

[0396] Accardi, L. et al., Int. J Cancer 134 (2014): 2742-2747 [0397] Aken, B. L. et al., Database. (Oxford) 2016 (2016) [0398] Alcoser, S. Y. et al., BMC. Biotechnol. 11 (2011): 124 [0399] Allison, J. P. et al., Science 270 (1995): 932-933 [0400] American Cancer Society, (2015a) [0401] American Cancer Society, (2015b) [0402] Ampie, L. et al., Front Oncol. 5 (2015): 12 [0403] Andersen, R. S. et al., Nat. Protoc. 7 (2012): 891-902 [0404] Anderson, D. M. et al., Cell 160 (2015): 595-606 [0405] Anderson, N. L. et al., J Proteome. Res 11 (2012): 1868-1878 [0406] Appay, V. et al., Eur. J Immunol. 36 (2006): 1805-1814 [0407] Armitage, J. O., Blood 110 (2007): 29-36 [0408] Aspden, J. L. et al., Elife. 3 (2014): e03528 [0409] Avigan, D. et al., Clin Cancer Res. 10 (2004): 4699-4708 [0410] Azevedo, R. et al., J Control Release 214 (2015): 40-61 [0411] Banchereau, J. et al., Cell 106 (2001): 271-274 [0412] Beatty, G. et al., J Immunol 166 (2001): 2276-2282 [0413] Beggs, J. D., Nature 275 (1978): 104-109 [0414] Benjamini, Y. et al., Journal of the Royal Statistical Society. Series B (Methodological), Vol. 57 (1995): 289-300 [0415] Berman, R. S. et al., National Cancer Institute: PDQ(R) Colon Cancer Treatment (2015a) [0416] Berman, R. S. et al., National Cancer Institute: PDQ(R) Rectal Cancer Treatment (2015b) [0417] Boulter, J. M. et al., Protein Eng 16 (2003): 707-711 [0418] Braumuller, H. et al., Nature (2013) [0419] Bray, F. et al., Int J Cancer 132 (2013): 1133-1145 [0420] Bridgewater, J. et al., J Hepatol. 60 (2014): 1268-1289 [0421] Brossart, P. et al., Blood 90 (1997): 1594-1599 [0422] Bruckdorfer, T. et al., Curr. Pharm. Biotechnol. 5 (2004): 29-43 [0423] Bujas, T. et al., Eur. J Histochem. 55 (2011): e7 [0424] Butterfield, L. H. et al., Clin. Cancer Res. 12 (2006): 2817-2825 [0425] Butterfield, L. H. et al., Clin. Cancer Res. 9 (2003): 5902-5908 [0426] Byrd, J. C. et al., N. Engl. J Med. 369 (2013): 32-42 [0427] Carballido, E. et al., Cancer Control 19 (2012): 54-67 [0428] Card, K. F. et al., Cancer Immunol. Immunother. 53 (2004): 345-357 [0429] Chang, Y. S. et al., Cancer Chemother. Pharmacol. 59 (2007): 561-574 [0430] Chapiro, J. et al., Radiol. Med. 119 (2014): 476-482 [0431] ClinicalTrials.gov, (2015) [0432] Cohen, C. J. et al., J Mol. Recognit. 16 (2003a): 324-332 [0433] Cohen, C. J. et al., J Immunol. 170 (2003b): 4349-4361 [0434] Cohen, S. N. et al., Proc. Natl. Acad. Sci. U.S.A 69 (1972): 2110-2114 [0435] Coligan, J. E. et al., Current Protocols in Protein Science (1995) [0436] Colombetti, S. et al., J Immunol. 176 (2006): 2730-2738 [0437] Coosemans, A. et al., Anticancer Res 33 (2013): 5495-5500 [0438] Counter, C. M. et al., Blood 85 (1995): 2315-2320 [0439] de, Klerk E. et al., Trends Genet. 31 (2015): 128-139 [0440] Dedes, K. J. et al., Sci. Transl. Med. 2 (2010): 53ra75 [0441] Dengjel, J. et al., Clin Cancer Res 12 (2006): 4163-4170 [0442] Denkberg, G. et al., J Immunol. 171 (2003): 2197-2207 [0443] Economopoulou, P. et al., Ann. Transl. Med. 4 (2016): 173 [0444] Eichhorst, B. F. et al., Blood 107 (2006): 885-891 [0445] Emens, L. A., Expert. Rev. Anticancer Ther. 12 (2012): 1597-1611 [0446] Enguita-German, M. et al., World J Hepatol. 6 (2014): 716-737 [0447] Estey, E. H., Am. J Hematol. 89 (2014): 1063-1081 [0448] Falk, K. et al., Nature 351 (1991): 290-296 [0449] Ferlay et al., GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11 [Internet], (2013), globocan.iarc.fr [0450] Follenzi, A. et al., Nat Genet. 25 (2000): 217-222 [0451] Fong, L. et al., Proc. Natl. Acad. Sci. U.S.A 98 (2001): 8809-8814 [0452] Forsey, R. W. et al., Biotechnol. Lett. 31 (2009): 819-823 [0453] Fuge, O. et al., Res Rep. Urol. 7 (2015): 65-79 [0454] Furman, R. R. et al., N. Engl. J Med. 370 (2014): 997-1007 [0455] Gabrilovich, D. I. et al., Nat. Med 2 (1996): 1096-1103 [0456] Gandhi, A. V. et al., Ann Surg. Oncol 20 Suppl 3 (2013): S636-S643 [0457] Gattinoni, L. et al., Nat. Rev. Immunol. 6 (2006): 383-393 [0458] Giannopoulos, K. et al., Leukemia 24 (2010): 798-805 [0459] Giannopoulos, K. et al., Int. J Oncol 29 (2006): 95-103 [0460] Gnjatic, S. et al., Proc Natl. Acad. Sci. U.S.A 100 (2003): 8862-8867 [0461] Godkin, A. et al., Int. Immunol 9 (1997): 905-911 [0462] Goede, V. et al., N. Engl. J Med. 370 (2014): 1101-1110 [0463] Gonzalez-Cao, M. et al., Cancer Biol Med 13 (2016): 483-488 [0464] Gragert, L. et al., Hum. Immunol. 74 (2013): 1313-1320 [0465] Granziero, L. et al., Blood 97 (2001): 2777-2783 [0466] Green, J. et al., Cochrane. Database. Syst. Rev (2005): CD002225 [0467] Green, M. R. et al., Molecular Cloning, A Laboratory Manual 4th (2012) [0468] Greenfield, E. A., Antibodies: A Laboratory Manual 2nd (2014) [0469] Grivas, P. D. et al., Semin Cancer Biol 35 (2015): 125-132 [0470] Gunawardana, C. et al., Br. J Haematol. 142 (2008): 606-609 [0471] Gustafsson, C. et al., Trends Biotechnol. 22 (2004): 346-353 [0472] Hallek, Michael et al., ASH Annual Meeting Abstracts 112 (2008): 325 [0473] Harig, S. et al., Blood 98 (2001): 2999-3005 [0474] Hinrichs, C. S. et al., Nat Biotechnol. 31 (2013): 999-1008 [0475] Holtl, L. et al., Clin. Cancer Res. 8 (2002): 3369-3376 [0476] Horig, H. et al., Cancer Immunol. Immunother. 49 (2000): 504-514 [0477] Hung, C. F. et al., Immunol. Rev 222 (2008): 43-69 [0478] Hus, I. et al., Oncol Rep. 20 (2008): 443-451 [0479] Hwang, M. L. et al., J Immunol. 179 (2007): 5829-5838 [0480] Inoue, H. et al., Int. J Cancer 63 (1995): 523-526 [0481] Jones, R. T. et al., Urol. Clin North Am. 43 (2016): 77-86 [0482] Jung, G. et al., Proc Natl Acad Sci USA 84 (1987): 4611-4615 [0483] Kalos, M. et al., Sci. Transl. Med 3 (2011): 95ra73 [0484] Kanthan, R. et al., J Oncol 2015 (2015): 967472 [0485] Kassiotis, G. et al., Philos. Trans. R Soc. Lond B Biol Sci. 372 (2017) [0486] Kaufman, H. L. et al., Clin Cancer Res. 14 (2008): 4843-4849 [0487] Khoury, G. A. et al., Sci. Rep. 1 (2011) [0488] Kibbe, A. H., Handbook of Pharmaceutical Excipients rd (2000) [0489] Kimura, H. et al., Int. J Oncol 30 (2007): 171-179 [0490] Knollman, H. et al., Ther. Adv. Urol. 7 (2015a): 312-330 [0491] Knollman, H. et al., Ther. Adv. Urol. 7 (2015b): 312-330 [0492] Koido, S. et al., World J Gastroenterol. 19 (2013): 8531-8542 [0493] Kono, K. et al., Cancer Sci. 100 (2009): 1502-1509 [0494] Krackhardt, A. M. et al., Blood 100 (2002): 2123-2131 [0495] Krieg, A. M., Nat. Rev. Drug Discov. 5 (2006): 471-484 [0496] Krishnamurthy, J. et al., Clin Cancer Res 21 (2015): 3241-3251 [0497] Kronenberger, K. et al., J Immunother. 31 (2008): 723-730 [0498] Kuball, J. et al., Blood 109 (2007): 2331-2338 [0499] Laumont, C. M. et al., Cell Mol. Life Sci. 75 (2018): 607-621 [0500] Lee, W. C. et al., J Immunother. 28 (2005): 496-504 [0501] Leitlinie Endometriumkarzinom, 032/034, (2008) [0502] Leitlinie Magenkarzinom, 032-0090L, (2012) [0503] Leitlinien für Diagnostik and Therapie in der Neurologie, 030/099, (2014) [0504] Li, Y. et al., Cancer Epidemiol. 39 (2015): 8-13 [0505] Liang, Z. et al., Zhonghua Zhong. Liu Za Zhi. 27 (2005): 534-537 [0506] Liddy, N. et al., Nat. Med. 18 (2012): 980-987 [0507] Liepe, J. et al., Science 354 (2016): 354-358 [0508] Ljunggren, H. G. et al., J Exp. Med 162 (1985): 1745-1759 [0509] Llovet, J. M. et al., N. Engl. J Med. 359 (2008): 378-390 [0510] Longenecker, B. M. et al., Ann N.Y. Acad. Sci. 690 (1993): 276-291 [0511] Lonsdale, J., Nat. Genet. 45 (2013): 580-585 [0512] Lukas, T. J. et al., Proc. Natl. Acad. Sci. U.S.A 78 (1981): 2791-2795 [0513] Lukka, H. et al., Clin Oncol (R Coll. Radiol.) 14 (2002): 203-212 [0514] Lundblad, R. L., Chemical Reagents for Protein Modification 3rd (2004) [0515] Mantia-Smaldone, G. M. et al., Hum. Vaccin. Immunother. 8 (2012): 1179-1191 [0516] Marten, A. et al., Cancer Immunol. Immunother. 51 (2002): 637-644 [0517] Massari, F. et al., Cancer Treat. Rev. 41 (2015): 114-121 [0518] Matsueda, S. et al., World J Gastroenterol. 20 (2014): 1657-1666 [0519] Maus, M. V. et al., Blood 123 (2014): 2625-2635 [0520] Mayr, C. et al., Exp. Hematol. 34 (2006): 44-53 [0521] Mayr, C. et al., Blood 105 (2005): 1566-1573 [0522] Meziere, C. et al., J Immunol 159 (1997): 3230-3237 [0523] Miyagi, Y. et al., Clin. Cancer Res. 7 (2001): 3950-3962 [0524] Molina, J. R. et al., Mayo Clin Proc. 83 (2008): 584-594 [0525] Morgan, R. A. et al., Science 314 (2006): 126-129 [0526] Mortara, L. et al., Clin Cancer Res. 12 (2006): 3435-3443 [0527] Moulton, H. M. et al., Clin Cancer Res. 8 (2002): 2044-2051 [0528] Mueller, L. N. et al., J Proteome. Res. 7 (2008): 51-61 [0529] Mueller, L. N. et al., Proteomics. 7 (2007): 3470-3480 [0530] Muller, M. R. et al., Blood 103 (2004): 1763-1769 [0531] Mumberg, D. et al., Proc. Natl. Acad. Sci. U.S.A 96 (1999): 8633-8638 [0532] Nam, J. W. et al., Mol. Cells 39 (2016): 367-374 [0533] National Cancer Institute, (Jun. 5, 2015) [0534] National Cancer Institute (NCI), (Jan. 19, 2011) [0535] Nilsen, T. W. et al., Nature 463 (2010): 457-463 [0536] O'Brien, S. et al., Lancet Oncol 15 (2014): 48-58 [0537] O'Leary, N. A. et al., Nucleic Acids Res 44 (2016): D733-D745 [0538] Ohigashi, Y. et al., Clin Cancer Res. 11 (2005): 2947-2953 [0539] Okuno, K. et al., Exp. Ther. Med. 2 (2011): 73-79 [0540] Olexiouk, V. et al., Nucleic Acids Res 44 (2016): D324-D329 [0541] Palma, M. et al., Cancer Immunol. Immunother. 57 (2008): 1705-1710 [0542] Palmer, D. H. et al., Hepatology 49 (2009): 124-132 [0543] Palomba, M. L., Curr. Oncol Rep. 14 (2012): 433-440 [0544] Parikh, S. A. et al., Blood 118 (2011): 2062-2068 [0545] Phan, G. Q. et al., Cancer Control 20 (2013): 289-297 [0546] Pinheiro, J. et al., nlme: Linear and Nonlinear Mixed Effects Models (CRAN.R-project.org/packe=nlme) (2015) [0547] Plebanski, M. et al., Eur. J Immunol 25 (1995): 1783-1787 [0548] Porta, C. et al., Virology 202 (1994): 949-955 [0549] Porter, D. L. et al., N. Engl. J Med. 365 (2011): 725-733 [0550] Quillien, V. et al., Anticancer Res. 17 (1997): 387-391 [0551] Quinn, D. I. et al., Urol. Oncol 33 (2015): 245-260 [0552] Rakic, M. et al., Hepatobiliary. Surg. Nutr. 3 (2014): 221-226 [0553] Rammensee, H. G. et al., Immunogenetics 50 (1999): 213-219 [0554] Reinisch, W. et al., J Immunother. 25 (2002): 489-499 [0555] Reinmuth, N. et al., Dtsch. Med. Wochenschr. 140 (2015): 329-333 [0556] Richards, S. et al., J Natl. Cancer Inst. 91 (1999): 861-868 [0557] Rini, B. I. et al., Curr. Opin. Oncol. 20 (2008): 300-306 [0558] Rini, B. I. et al., Cancer 107 (2006): 67-74 [0559] Robak, T. et al., Expert. Opin. Biol. Ther 14 (2014): 651-661 [0560] Rock, K. L. et al., Science 249 (1990): 918-921 [0561] Rodenko, B. et al., Nat. Protoc. 1 (2006): 1120-1132 [0562] Rouanne, M. et al., Crit Rev Oncol Hematol. 98 (2016): 106-115 [0563] Rucki, A. A. et al., World J Gastroenterol. 20 (2014): 2237-2246 [0564] S3-Leitlinie Exokrines Pankreaskarzinom, 032-0100L, (2013) [0565] S3-Leitlinie Lungenkarzinom, 020/007, (2011a) [0566] S3-Leitlinie Lungenkarzinom, 020/007, (2011b) [0567] S3-Leitlinie maligne Ovarialtumore, 032-0350L, (2013) [0568] S3-Leitlinie Mammakarzinom, 032-0450L, (2012) [0569] S3-Leitlinie Melanom, 032-0240L, (2013) [0570] S3-Leitlinie Prostatakarzinom, 043/0220L, (2014) [0571] S3-Leitlinie Zervixkarzinom, 032/0330L, (2014) [0572] Saiki, R. K. et al., Science 239 (1988): 487-491 [0573] Salman, B. et al., Oncoimmunology. 2 (2013): e26662 [0574] Sangro, B. et al., J Clin. Oncol. 22 (2004): 1389-1397 [0575] Schetelig, J. et al., J Clin Oncol 26 (2008): 5094-5100 [0576] Schiavetti, F. et al., Cancer Res 62 (2002): 5510-5516 [0577] Schmidt, S. M. et al., Cancer Res. 64 (2004): 1164-1170 [0578] Schmitt, T. M. et al., Hum. Gene Ther. 20 (2009): 1240-1248 [0579] Scholten, K. B. et al., Clin Immunol. 119 (2006): 135-145 [0580] Seeger, F. H. et al., Immunogenetics 49 (1999): 571-576 [0581] Sherman, F. et al., Laboratory Course Manual for Methods in Yeast Genetics (1986) [0582] Shi, M. et al., World J Gastroenterol. 10 (2004): 1146-1151 [0583] Showel, M. M. et al., F1000Prime. Rep. 6 (2014): 96 [0584] Siegel, S. et al., Blood 102 (2003): 4416-4423 [0585] Silva, L. P. et al., Anal. Chem. 85 (2013): 9536-9542 [0586] Singh-Jasuja, H. et al., Cancer Immunol. Immunother. 53 (2004): 187-195 [0587] Small, E. J. et al., J Clin Oncol. 24 (2006): 3089-3094 [0588] Spaner, D. E. et al., Cancer Immunol. Immunother. 54 (2005): 635-646 [0589] Srivastava, N. et al., Cancer Manag. Res. 6 (2014): 279-289 [0590] Stahl, M. et al., Ann. Oncol. 24 Suppl 6 (2013): vi51-vi56 [0591] Steinberg, R. L. et al., Urol. Oncol (2016a) [0592] Steinberg, R. L. et al., Urol. Oncol (2016b) [0593] Stevanovic, S. et al., J Clin Oncol 33 (2015): 1543-1550 [0594] Stintzing, S., F1000Prime. Rep. 6 (2014): 108 [0595] Sturm, M. et al., BMC. Bioinformatics. 9 (2008): 163 [0596] Su, Z. et al., Cancer Res. 63 (2003): 2127-2133 [0597] Subramanian, R. P. et al., Retrovirology. 8 (2011): 90 [0598] Takayama, T. et al., Cancer 68 (1991): 2391-2396 [0599] Takayama, T. et al., Lancet 356 (2000): 802-807 [0600] Tanaka, F. et al., Int. J Oncol 10 (1997): 1113-1117 [0601] Teufel, R. et al., Cell Mol. Life Sci. 62 (2005): 1755-1762 [0602] Thakkar, J. P. et al., Cancer Epidemiol. Biomarkers Prev. 23 (2014): 1985-1996 [0603] Toh, U. et al., Int. J Clin Oncol 7 (2002): 372-375 [0604] Toh, U. et al., Clin Cancer Res. 6 (2000): 4663-4673 [0605] Toomey, P. G. et al., Cancer Control 20 (2013): 32-42 [0606] Tran, E. et al., Science 344 (2014): 641-645 [0607] Vanderperre, B. et al., PLoS. One. 8 (2013): e70698 [0608] Vici, P. et al., J Exp. Clin Cancer Res 33 (2014): 29 [0609] Von Hoff, D. D. et al., N. Engl. J Med. 369 (2013): 1691-1703 [0610] von Rundstedt, F. C. et al., Transl. Androl Urol. 4 (2015): 244-253 [0611] Walter, S. et al., J. Immunol. 171 (2003): 4974-4978 [0612] Walter, S. et al., Nat Med. 18 (2012): 1254-1261 [0613] Wang, N. et al., Arch. Gynecol. Obstet. 283 (2011): 103-108 [0614] Wierda, W. G. et al., Blood 118 (2011): 5126-5129 [0615] Wilhelm, S. M. et al., Cancer Res. 64 (2004): 7099-7109 [0616] Willcox, B. E. et al., Protein Sci. 8 (1999): 2418-2423 [0617] Wilson, P. M. et al., Nat Rev. Clin Oncol 11 (2014): 282-298 [0618] Wittig, B. et al., Hum. Gene Ther. 12 (2001): 267-278 [0619] World Cancer Report, (2014) [0620] World Health Organization, (2014) [0621] Zaremba, S. et al., Cancer Res. 57 (1997): 4570-4577 [0622] Zufferey, R. et al., J Virol. 73 (1999): 2886-2892