EARLY DETECTION OF PANCREATIC CANCER

Abstract
This document provides methods and materials involved in the early detection of pancreatic cancer. For example, this document provides methods and materials for assessing nucleic acid obtained from a blood sample of a human for a CpG methylation site profile that, at least in part, indicates that the human has pancreatic cancer.
Description
BACKGROUND

1. Technical Field


This document relates to methods and materials involved in the early detection of pancreatic cancer. For example, this document provides methods and materials for assessing nucleic acid obtained from a blood sample of a human for a CpG methylation site profile that, at least in part, indicates that the human has pancreatic cancer.


2. Background Information


Pancreatic cancer (PaC) is the 10th most common tumor type for men and women in yearly incidence in the United States and the fourth leading cause of cancer mortality (Jemal et al., CA Cancer J. Clin., 60(5):277-300 (2010)). PaC is associated with a very poor prognosis as it remains one of the most difficult tumors to treat. Much of this may be attributed to the late stage at which cancer is usually detected. Between 1999 and 2006, only 8% of patients were diagnosed, often by incidental finding on radiologic imaging, at a localized stage where immediate surgical resection and subsequent cure could be considered.


SUMMARY

This document relates to methods and materials involved in the early detection of pancreatic cancer. For example, this document provides methods and materials for assessing nucleic acid obtained from a blood sample of a human for a CpG methylation site profile that, at least in part, indicates that the human has pancreatic cancer.


As described herein, nucleic acid from blood cells of humans with pancreatic cancer can contain different levels of the methylation CpG sites listed in Table 1 or 5 when compared to the level of methylation of those CpG sites in nucleic acid from blood cells of humans without pancreatic cancer. In particular, the methylation change in at least three methylation CpG sites listed in Table 1 or 5 (e.g., IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites) can indicate that a human has pancreatic cancer. In some cases, detecting a reduction or low level of methylation of the LCN2_P86 site can indicate that the human has resectable pancreatic cancer.


The methods and materials provided herein can allow clinicians to detect humans with pancreatic cancer at an early stage without the need to obtain invasive tissue biopsies (e.g., pancreas tissue biopsies). Such an early detection can allow patients to be treated sooner with the hopes that a successful treatment outcome will be achieved.


In general, one aspect of this document features a method for identifying a human as having pancreatic cancer. The method comprises, or consists essentially of, (a) determining whether or not nucleic acid obtained from a blood sample of a human comprises at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer, wherein the at least three methylation CpG sites are selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites, and (b) classifying the human as having pancreatic cancer if the nucleic acid comprises the at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer, and classifying the human as not having pancreatic cancer if the nucleic acid does not comprise the at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer. The blood sample can be a blood sample obtained from a human not subjected to a prior pancreas tissue biopsy. The method can comprise determining whether or not nucleic acid obtained from the blood sample comprises at least four methylation CpG sites that have an altered methylation status indicative of pancreatic cancer. The at least four methylation CpG sites can be selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites. The method can comprise determining whether or not nucleic acid obtained from the blood sample comprises at least five methylation CpG sites that have an altered methylation status indicative of pancreatic cancer. The at least five methylation CpG sites can be selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites.


In another aspect, this document features a method for identifying a human as having pancreatic cancer. The method comprises, or consists essentially of, (a) detecting the presence of at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer in nucleic acid obtained from a blood sample of a human, wherein the at least three methylation CpG sites are selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites, and (b) classifying the human as having pancreatic cancer based at least in part on the presence of the at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer. The blood sample can be a blood sample obtained from a human not subjected to a prior pancreas tissue biopsy. The method can comprise detecting the presence of at least four methylation CpG sites that have an altered methylation status indicative of pancreatic cancer in the nucleic acid. The at least four methylation CpG sites can be selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites. The method can comprise detecting the presence of at least five methylation CpG sites that have an altered methylation status indicative of pancreatic cancer in the nucleic acid. The at least five methylation CpG sites can be selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites.


In another aspect, this document features a method for identifying a human as having resectable pancreatic cancer. The method comprises, or consists essentially of, (a) determining whether or not nucleic acid obtained from a blood sample of a human comprises hypomethylation of an LCN2_P86 methylation CpG site, and (b) classifying the human as having resectable pancreatic cancer if the nucleic acid comprises the hypomethylation of the LCN2_P86 methylation CpG site, and classifying the human as not having resectable pancreatic cancer if the nucleic acid does not comprise the hypomethylation of the LCN2_P86 methylation CpG site.


In another aspect, this document features a method for identifying a human as having resectable pancreatic cancer. The method comprises, or consists essentially of, (a) detecting hypomethylation of an LCN2_P86 methylation CpG site of nucleic acid obtained from a blood sample of a human, and (b) classifying the human as having resectable pancreatic cancer based at least in part on the hypomethylation.


Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Although methods and materials similar or equivalent to those described herein can be used to practice the invention, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.


The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.





DESCRIPTION OF THE DRAWINGS


FIG. 1: Methylation level agreement between phase I and phase II. Representative Bland-Altman graph in one subject demonstrates good agreement between phase I and phase II data in most 96 CpG sites. Each dot represents one CpG site. Mean methylation level for each CpG site (from 0 to 100%) is shown in x-axis. Methylation level difference for each CpG site between phase I and phase II is shown in y-axis. The dashed lines indicate 95% confidence interval for the difference between the two assays, and the solid line indicates the average differences between the two assays.



FIG. 2: Validation of 96 selected CpG sites. Scatter plot shows reproducible methylation differences between phase I and phase II. Wilcoxon Rank Sum z-values were plotted on x-axis (phase I) and y-axis (phase II). 88 of the 96 CpG sites were validated by p value (<0.05) and direction (hyper/hypo-methylation). Although 8 CpG sites were not statistically significant, the trends in both phases are all the same.





DETAILED DESCRIPTION

This document provides methods and materials involved in the early detection of pancreatic cancer. For example, this document provides methods and materials for assessing nucleic acid obtained from a blood sample of a human for a CpG methylation site profile that, at least in part, indicates that the human has pancreatic cancer.


As described herein, nucleic acid from blood samples of humans with pancreatic cancer can contain different levels of methylation at particular CpG sites (e.g., the methylation CpG sites listed in Table 1 or the methylation CpG sites listed in Table 5) when compared to nucleic acid from blood samples of humans without pancreatic cancer. The methylation level change in these methylated CpG sites can be used to identify humans with pancreatic cancer. For example, the methylation level changes in at least three (e.g., at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least ten) methylation CpG sites listed in Table 1 or Table 5 can indicate that a human has pancreatic cancer. Methylation level changes in these methylation CpG sites listed in Table 1 can indicate that a human has pancreatic cancer. In some cases, a reduction in the level of methylation at the LCN2_P86 site for a human with pancreatic cancer, as compared to the level observed in healthy humans, can indicate that the human has resectable pancreatic cancer.









TABLE 1







Selected CpG sites.


















Methylation




Gene
GenBank ®
GenBank ®

change in
SEQ


Illumina ID
Symbol
Accession No.
GI No.
Sequence of CpG region
cancer patients
ID NO:
















JAK3_P1075_R
JAK3
NM_000215.2
47157314
AACAAAGAAAGCCAGGGTGTCA
hypomethylation
 1






GGACAGGCACAGACTGGAACTT








GGACC[CG]AGGCAGGACAGGG








AGCTGGCCAGGGAAAGGGTGCT








CCAGGAGGAGGGCA







SLC5A5_E60_F
SLC5A5
NM_000453.1
4507034
TGAGCACAGCGCCCAGGGAGAG
hypomethylation
 2






GGACAGACAGCCGGCTGCATGG








GACAG[CG]GAACCCAGAGTGA








GAGGGGAGGTGGCAGGACAGAC








AGACAGCAGGGGCG







HPN_P374_R
HPN
NM_182983.1
33695154
GGGGCAGCGGCCCCGCACCCCT
hypomethylation
 3






CCTCCTTGCTGATTTGCACACA








TTGGC[CG]CTTCAGACACGCA








CTTCTGGGGCCAGCCCCTCCCC








GCCTCCTCCCTGCC







AXL_E61_F
AXL
NM_021913.2
21536465
GGAGGAATGTTTACCAGACACA
hypomethylation
 4






GAGCCCAGAGGGACAGCGCCCA








GAGCC[CG]GATAGAGAGACAC








GGCCTCACTGGCTCAGGACAGG








GGGCACAGCCACCA







CEACAM1_P44_R
CEACAM1
NM_001712.3
68161539
GAGCCTCCTCCCTGGGGCCCAG
hypomethylation
 5






AGCTTTGTCTGATCATGTGTGC








TGGGG[CG]GGGTTTGTCCAGG








AAGCTCTGTTTCCTCTCCTCTC








ATTCCTACCTTTGT







TIE1_E66_R
TIE1
NM_005424.2
31543809
GGCCCACAGCATCTGACCCCAG
hypomethylation
 6






GCCCAGCTCGTCCTGGCTGGCC








TGGGT[CG]GCCTCTGGAGTAT








GGTCTGGCGGGTGCCCCCTTTC








TTGCTCCCCATCCT







PI3_P274_R
PI3
NM_002638.2
31657130
TGGTTTTGTAATCAAGACTGGA
hypomethylation
 7






TCTACCAGTGACTTGCTGAATA








ACCTT[CG]GTGATTCCTTTCT








CTTCTTGGGTCTCACTGTATTT








CAAAACATGAAGAA







MMP9_P189_F
MMP9
NM_004994.2
74272286
GCGGTTTCCTGCGGGTCTGGGG
hypomethylation
 8






TCTTGCCTGACTTGGCAGTGGA








GACTG[CG]GGCAGTGGAGAGA








GGAGGAGGTGGTGTAAGCCCTT








TCTCATGCTGGTGC







IFNGR2_P377_R
IFNGR2
NM_005534.2
47419933
TGGGAAGAGCAAAAGAAAAGCT
hypomethylation
 9






CTATGTTGCAAAACCCATTTTT








GCTAA[CG]TGTCCAGTGGGCT








CCCGGGACGACCTGTTTTTAAA








TTCTTGGTCTCCCT







HIC_1_SEQ_48_S103_R
HIC1
NM_006497.2
61676185
CCCCCGGCCGCCCCGACGGGCC
hypomethylation
10






TAGTCTCCTCTATCGCTGGATG








AAGCA[CG]AGCCGGGCCTGGG








TAGCTATGGCGACGAGCTGGGC








CGGGAGCGCGGCTC







MPL_P62_F
MPL
NM_005373.1
4885490
CCCCAGTGTGGTCTGGATGGGC
hypomethylation
11






CCCAGAGGGGCAGGGACAGGGA








CAGGA[CG]TGGGGCTGTATCT








GACAGGAACCTGAGGGGCTGGC








CTGGGAGGGGATTG







TAL1_P817_F
TAL1
NM_003189.1
4507362
GCGTGTTCGCTGGGGGTTAATG
hypomethylation
12






TTTGCCTTATGACCAAGTCTCT








GTGTC[CG]TGCCTCTCTCCAT








TTTCTCTTCCTACCTCAAACCC








AGCAACTTAGAAAA







DHCR24_P652_R
DHCR24
NM_014762.2
56790943
GGCTGGCACTCTTCCTCTTTTT
hypomethylation
13






CCAGTTCACTGAGGCAGATGGG








AGGCC[CG]GAGGAGAAAGAAT








GAAGGAAGGCATTTCAGCCCGA








GTAAACTCCCCAGG







EPHA2_P203_F
EPHA2
NM_004431.2
32967310
TGGACTCGCGGGCTCCCCGCAG
hypomethylation
14






GCCTTCCAAAGTTTGAGCGTCT








CAAAG[CG]CCAGCGCCCCTAC








GGATTAGCCCCCAGGGATCTCT








GAGCCTGGTATCCT







GFI1_P208_R
GFI1
NM_005263.2
71037376
ACGCGGGCTCTGCCACCGCCTG
hypomethylation
15






AGGTCATACCCAGGCACTGGGT








GTTGG[CG]GGAGCAGTAAAGC








GCCATAAAAGCACCACTTGGAT








GACTATTGCAAAGT







GSTM2_P453_R
GSTM2
NM_000848.2
23065549
GATAAGTGACAGTGAGTTATAA
hypomethylation
16






TCATCCTTGCCTGTGTTGTCCT








TCCCA[CG]TTAGGTCTGTCAT








GCCACGTATGTCCGCAGTTTAT








AACAATCTCTATCA







AIM2_E208_F
AIM2
NM_004833.1
4757733
TCGTCTCTAACCCAGCTCCTCT
hypermethylation
17






ATGGTGCTTACCTCCTGATCCC








TGGGG[CG]ATCAGCAAACCGG








GTCTGCCACCTTCTTTTCAGAG








AGCTTAACTAGCAG







AIM2_P624_F
AIM2
NM_004833.1
4757733
TGATATTAAGGGCATAATGAAG
hypomethylation
18






CTAAGGGTCAGCAGTCAGCCAA








GTTTT[CG]ACCATCTTGGCTT








TAACCAGTTGCGGCCAGTTTCT








TCTGTGTTACATTC







IL10_P85_F
IL10
NM_000572.2
24430216
AGCTCAGGGAGGCCTCTTCATT
hypomethylation
19






CATTAAAAAGCCACAATCAAGG








TTTCC[CG]GCACAGGATTTTT








TCTGCTTAGAGCTCCTCCTTCT








CTAACCTCTCTAAT







IL10_P348_F
IL10
NM_000572.2
24430216
GAGGCCCTCAGCTGTGGGTTCT
hypomethylation
20






CATTCGCGTGTTCCTAGGTCAC








AGTGA[CG]TGGACAAATTGCC








CATTCCAGAATACAATGGGATT








GAGAAATAATTGGG







VAMP8_P241_F
VAMP8
NM_003761.2
14043025
AAAAAAAGGCTGCCCTTTCTAG
hypomethylation
21






ATCAGGAGGTCCAGCCTCTGGA








AACCT[CG]GAGGGCTGCTTGA








TCTTTCTTTTCTAATTCCTGAC








AAGTTAGAAGACCT







ZAP70_P220_R
ZAP70
NM_001079.3
46488942
ACTGCTGCCTACCCTCCGGTTC
hypermethylation
22






CAGGTATGCAGGCTTCCTCCCT








TCTGA[CG]GTTCCTGCTGCTG








GAGTCGTCCTTCCTGAAACCCT








GCCTTTGCTTAGCC







IL1RN_P93_R
IL1RN
NM_173843.1
27894320
GTCACCCTCCTGGAAACTGGGC
hypermethylation
23






CTGCTTGGCATCAAGTCAGCCA








TCAGC[CG]GCCCATCTCCTCA








TGCTGGCCAACCCTCTGTGAGT








GTGTGGGAGGGGAG







PADI4_P1011_R
PADI4
NM_012387.1
6912575
CCCAGGTGCAACCACAGCTCTG
hypermethylation
24






AGGCCACATGGGCATCCCCCTG








GCAGG[CG]TGGCCCACACCTG








CACTGTCTGGTCTGACACCCAG








AGGCCCTGGCAAGA







ERCC3_P1210_R
ERCC3
NM_000122.1
4557562
TCTTGAAGAGCCTTGGTAGAAG
hypomethylation
25






TATGGGCATTAAAGGTGATTCT








GGTGA[CG]GCTCAGATGGAAA








GGAGAAATATGTTATTGAAACT








GGAGGCAAGTGGTA







CASP10_P334_F
CASP10
NM_001230.3
47078266
TCGCTCCATTGTTTATTTGCAT
hypomethylation
26






GTGGACATAAGAAAGGGTTAAC








ATGGC[CG]ACAACTATTTCAT








GAGCTTTTTGGCTTTATTTGAA








AAGTGAAGTGTGTT







CTLA4_E176_R
CTLA4
NM_005214.2
21361211
AAGACCTGAACACCGCTCCCAT
hypermethylation
27






AAAGCCATGGCTTGCCTTGGAT








TTCAG[CG]GCACAAGGCTCAG








CTGAACCTGGCTACCAGGACCT








GGCCCTGCACTCTC







IGFBP5_P9_R
IGFBP5
NM_000599.2
46094066
TTCCTAGCTCTTTTCCCCTGCA
hypomethylation
28






GAAGTTTCCAAAGAGACTACGG








GGCTC[CG]GGAGAGCAGGCGC








TTTTAAATAGCCGGCCCCTGGC








TGCCAGCCAGTTTG







AGXT_P180_F
AGXT
NM_000030.1
4557288
AAGAAACACTTCTCTCACCCCT
hypomethylation
29






GAGCTAAGCAGAATAAGAGGGG








CTGGA[CG]TGCAGGACTCAGA








GTGGGAGCGAGGAGGGCTGGGG








TGAGGACAGCTTTG







PTHR1_P258_F
PTHR1
NM_000316.2
39995096
TAAGAGAGAGGCATGGCAGGGC
hypermethylation
30






AAGGAGAGGACTATTGAGGCAC








ACACA[CG]TGTCTGGCAGCCT








GAGTGGGCCCAGTTACCTGGCA








GGCAGACCCATGGG







ZMYND10_P329__F
ZMYND10
NM_015896.2
37594443
CCCGCTGCTCTTCCTCCTCCTT
hypomethylation
31






ATGGCTTCTTGGTTCCTCTATT








TCTCG[CG]TCCCGGCTCCACT








AGTTGGCTCCTGAAATACTGCC








AGGGCGCACGACTT







IL17RB_E164_R
IL17RB
NM_018725.2
27477073
CCAGCACCTCTTCCCTCATCTC
hypomethylation
32






CCGGCCCTCGAGCCCAGATCCT








GACGT[CG]TCTGATCCGCCAG








TCCAGGCTGCCCCGAAGGCGTG








CGCGGACTGCCGGC







CD86_P3_F
CD86
NM_006889.2
29029570
GAACAGCTTCTCTTAAAGAAAG
hypomethylation
33






TTAGCTGGGTAGGTATACAGTC








ATTGC[CG]AGGAAGGCTTGCA








CAGGGTGAAAGCTTTGCTTCTC








TGCTGCTGTAACAG







PADI4_E24_F
PADI4
NM_012387.1
6912575
AGGAACCAGCCCAGGGGCTTCC
hypomethylation
34






TACAGCCAGAGGGACGAGCTAG








CCCGA[CG]ATGGCCCAGGGGA








CATTGATCCGTGTGACCCCAGA








GCAGCCCACCCATG







RHOH_P953_R
RHOH
NM_004310.2
45827772
GCCAACCTCTTTCCCACCTCAG
hypermethylation
35






GGCCTTTGCACATACTATTTGC








CTCTA[CG]TGGAATGTTCTTT








CCTCCTTCTCATCCATTAGAGT








GGCAGCAGTACTTT







FGF1_P357_R
FGF1
NM_033136.1
15055540
CAGGAACACAGAGCCATTGGCC
hypermethylation
36






AGCCAGGAGGGAGGTAGAGACA








GAAGA[CG]GTGGCAGCAGCTA








CCCTGGGTGTTATTTTAACGTG








GTTTGTCTTGGGGC







CSF1R_E26_F
CSF1R
NM_005211.2
27262658
TCCTCTTCCTCTTCTCTCTTCT
hypomethylation
37






CCACCTTCTCCTCACTTCGTGC








TCTCA[CG]CTTTTGGACACTC








TGTCTGCCCTTCTCCTACCTGG








GGCCTGATCATGAC







SPARC_P195_F
SPARC
NM_003118.2
48675809
GGTGGGCTGTCCTGACCAAACG
hypomethylation
38






TCCCAACCCTGCCTGCCTCATC








TGTTC[CG]GGGCTGCTGCCTA








AACCGACTCACAGAGTGCCAGG








GCTGGACAGGCCTG







ITK_P114_F
ITK
NM_005546.3
21614549
TTTTTTACATATGCCTCCTCGT
hypermethylation
39






TTTGTGAATTTTGAAAGGATGT








GGTTT[CG]GCCTTTGACATCA








GAGGAGAAGCTCAGCTATGTTG








GCTGAACGTTGATA







ITK_E166_R
ITK
NM_005546.3
21614549
CAAGAAATCCCAACAAAAGAGA
hypermethylation
40






AGAACTTCTCCCTCGAACTTTA








AAGTC[CG]CTTCTTTGTGTTA








ACCAAAGCCAGCCTGGCATACT








TTGAAGATCGTCAT







LTA_P214_R
LTA
NM_000595.2
6806892
CTCCCAGCCCACGATTCCCCTG
hypermethylation
41






ACCCGACTCCCTTTCCCAGAAC








TCAGT[CG]CCTGAACCCCCAG








CCTGTGGTTCTCTCCTAGGCCT








CAGCCTTTCCTGCC







NOTCH4_E4_F
NOTCH4
NM_004557.3
55770875
TCTGCTCCCACTGCCCCTCTTC
hypomethylation
42






TTCCTCCTCGGCCTGCTGCAAG








CCTCA[CG]TCTGAGCTGTTTC








CTGAGTCACACAATGTCCTGGA








CACCCTAGTAATGG







NOTCH4_P938_F
NOTCH4
NM_004557.3
55770875
GTTGAGGCACTCATGGCTGCTG
hypermethylation
43






CTGGTGCACCTGAGAGCCTTCC








CCTAC[CG]GGGAATATACTTC








ACCAGCACCACTTTCTTCCTTT








TTTTAGCTTTTTAT







RUNX3_E27_R
RUNX3
NM_001031680.1
72534651
ATCATTAGATGGCGGGAAGGGG
hypermethylation
44






CTTTCGGCAGCCAGGGTGGAGG








AGCTC[CG]AAGCTGACAGAGC








AGAGTGGGCCGCCTCCAGTGCC








ACGGGGAATGAATG







GPR116_P850_F
GPR116
NM_015234.3
44771172
CCTCTGCAGCGCTCCCTTTCCC
hypermethylation
45






TTTCCCTTTCCTGGTTCTCAAG








GCTCC[CG]AGCTTATGCCTTT








TCTCCTTCTATGCTCCCATCCT








CATCATCCTGCAGC







RAB32_E314_R
RAB32
NM_006834.2
20127508
TGGTGATCGGCGAGCTTGGCGT
hypomethylation
46






GGGCAAGACCAGCATCATCAAG








CGCTA[CG]TCCACCAGCTCTT








CTCCCAGCACTACCGGGCCACC








ATCGGGGTGGACTT







ESR1_P151_R
ESR1
NM_000125.2
62821793
GGCACATAAGGCAGCACATTAG
hypomethylation
47






AGAAAGCCGGCCCCTGGATCCG








TCTTT[CG]CGTTTATTTTAAG








CCCAGTCTTCCCTGGGCCACCT








TTAGCAGATCCTCG







IL6_P213_R
IL6
NM_000600.1
10834983
AAGAAAGTAAAGGAAGAGTGGT
hypomethylation
48






TCTGCTTCTTAGCGCTAGCCTC








AATGA[CG]ACCTAAGCTGCAC








TTTTCCCCCTAGTTGTGTCTTG








CCATGCTAAAGGAC







CLDN4_P1120_R
CLDN4
NM_001305.3
34335232
CTCCCCAGCCCAGTCTCTGGTC
hypermethylation
49






AAACTGGATTCCTGGCTGTTCC








CAGAA[CG]AGCTGCCTTTCCC








CACCTTGCCACCTCTGCCCTTG








TTCTCTCTGCCTGA







HGF_E102_R
HGF
NM_001010933.1
58533164
GGGCTGGCGGATCCCTCTGGAG
hypomethylation
50






GAGATGCCTGGGTGAAAGAATC








CTGTT[CG]GAGTCAGTGCCTA








AAAGAGCCAGTCGGCTCTGAGC








TGCTTTTTATTGCG







TFPI2_P152_R
TFPI2
NM_006528.2
31543803
ACCCCGCCGCCCCCGCGCTGCA
hypomethylation
51






AACTGTGTAAGAGGGAGAGGAA








TTCCC[CG]CCAAGTTGAAAAG








TTGAACCTGCCTCCCAAACTTT








CTCCTGTAGTCCAG







TRIP6_P1274_R
TRIP6
NM_003302.1
23308730
TCCTGCTGCAGATGGCAACCAT
hypomethylation
52






CTTGGGCATGGTGCCCGCTTGG








CATAG[CG]CCCGGCTCCGGAT








CTTCCTGTGCCTGGGGCCTCGG








GAGGCGCCTGGGGC







RUNX3_P247_F
RUNX3
NM_001031680.1
72534651
CACAGGATGCGAGAAGCCTGCT
hypermethylation
53






CGCGGCCTTGGCTCATTGGCTG








GGCCG[CG]GTCACCTGGGCCG








TGATGTCACGGCCTTTTAGAAG








ATCTTGTGGCTGCC







TRIP6_P1090_F
TRIP6
NM_003302.1
23308730
GGCTGGGGAACCCGAGGCGGAG
hypomethylation
54






GAGGAAGGGGACTTTGTGAACA








GTGGG[CG]GGGAGACGCAGAG








GCAGAGGCCCTGGCACGCAGCG








CCAACGCCCTGGTT







CPA4_E20_F
CPA4
NM_016352.2
61743915
AGACTCTTTATAAATACAGCTT
hypermethylation
55






GACTCAGCCACTGTATGACTGA








CTCCC[CG]GGGACATGAGGTG








GATACTGTTCATTGGGGCCCTT








ATTGGGTCCAGCAT







SYK_P584_F
SYK
NM_003177.3
34147655
CCATTCTTAGGGCTATAGGTTT
hypomethylation
56






AATTTATTTGGTTGTGGACGTC








AGAGC[CG]TCATGGTAAGAAG








GAAGCAAAGCCTTTTGTAATAA








TTAAAGCCTTCAGA







LCN2_P141_R
LCN2
NM_005564.2
38455401
GTTGTCCCTGCCAGAGGTGCAG
hypomethylation
57






CACTCCGGGAATGTCCCTCACT








CTCCC[CG]TCCCTCTGTCTTG








CCCAATCCTGACCAGGTGCAGA








AATCTTGCCAAGTG







LCN2_P86_R
LCN2
NM_005564.2
38455401
TCTGTCTTGCCCAATCCTGACC
hypomethylation
58






AGGTGCAGAAATCTTGCCAAGT








GTTTC[CG]CAGGAGTTGCTGG








CAATTGCCTCACATTCCTGGCC








TTGGCAAAGAATGA







SLC22A18_P472__R
SLC22A18
NM_002555.3
34734074
TGCCCAGCGCTCCCAGGGTCAC
hypomethylation
59






CCCTCTCTCTAGACTCACTTTC








TGCCC[CG]TCACCCCACTGTA








CACCCTTGGTCCCAGCCCCTTC








CAGTGGCTCAGCTT







SLC22A18P216_R
SLC22A18
NM_002555.3
34734074
AGATGAGCCAAAGCCCTTCCTT
hypomethylation
60






CCTCCAGTCAGCCTGGATCCTC








TCATC[CG]GCAGAACTGTCGC








CTTGCTTCTCTGAAGCGGTGAA








TGCCCTGGGGCTGG







RUNX3_P393_R
RUNX3
NM_001031680.1
72534651
GAGAAATAGAAAAGTGATGGCT
hypermethylation
61






TTTATTTGTGAGGCTGGCCTCA








GCACG[CG]GCCCAAGAAACAG








AACTGAAAGCGGTTGCAGTGGG








CGTGGCCAGGAGGG







LMO2_E148_F
LMO2
NM_005574.2
6633806
TTGGTGGCCTGGTTGTCTATCT
hypomethylation
62






GATAGGGCGGAGCCTTCACCCT








TGCAG[CG]AGCTCTCTCACAC








CAGATGTGCTCTGCGTGGAATC








CTAGGCCATCAGGG







LMO2_P794_R
LMO2
NM_005574.2
6633806
CAGCTACCTCCCCCGCATGCAT
hypomethylation
63






GTCTGTCTGCTGGGCAAGGCCC








AATTC[CG]AGGTGACAGCTCA








CCGGGCCTCACCCACAAGTCTC








TTCCAAGCATTAGC







CD82_P557_R
CD82
NM_002231.3
67782352
GATTCAATCAATGGTAGTCAGT
hypomethylation
64






ATTTTCAAAAAGTTCCTGGGCC








CAGGC[CG]CCTCCTGATAGAG








GCCCCGACTTAGGACACAAACC








GCTCCCACGCCGTT







SPI1_E205_F
SPI1
NM_003120.1
4507174
GAGTCCCGGTACTCACAGGGGG
hypomethylation
65






GACGAGGGGAAACCCTTCCATT








TTGCA[CG]CCTGTAACATCCA








GCCGGGCTCCGAGTCGGTCAGA








TCCCCTGCCTCGGT







SPI1_P48_F
SPI1
NM_003120.1
4507174
TTATCGAAGGGCCTGCCGCTGA
hypomethylation
66






GGAGATAGTCCCCTTGGGGTGC








ATCAC[CG]CCCCAACCCGTTT








GCATAAATCTCTTGCGCTACAT








ACAGGAAGTCTCTG







KCNK4_E3_F
KCNK4
NM_016611.2
15718764
CCGATCCGGTAATGGGCCTGGG
hypomethylation
67






AGATGCCAGATTAGCGTGGTGC








CTGTC[CG]GAGAGACGGGCCA








GCTGATGCCCAGGTCGGGGCCC








TGCCGCTGGCCACA







MMP8_E89_R
MMP8
NM_002424.1
4505220
CAGGAAAGGCCTTGGAAATCTG
hypomethylation
68






CACATGGAGTAAGAGCAGAAAT








GGAAG[CG]TCTTCAGGGAGAA








CATGATCTTCTCTTCAAACTCT








ACCCCTCCTGGCTT







CD9_P585_R
CD9
NM_001769.2
21237762
TTTGCTAATTACTTCCAAAAGC
hypomethylation
69






CTCCCATCTGTCATCCCACCCA








GACTG[CG]CGCTTCTAATTCC








TCCTACCCCACATGCTGTGCCC








AATGAAAAGTATGG







CD9_P504_F
CD9
NM_001769.2
21237762
TGCCCAATGAAAAGTATGGTCA
hypomethylation
70






GCGAGCGAAGGTTTGCAAGGAG








ACAGA[CG]AGGGCGAAATTAA








GCCAGGCGGCTTCCCTTTAAAT








CCTCGCAAAGCAGA







LCK_E28_F
LCK
NM_005356.2
20428651
GCAGCCAGGTTAGGCCAGGAGG
hypermethylation
71






ACCATGTGAATGGGGCCAGAGG








GCTCC[CG]GGCTGGGCAGGTA








AGGAGCGCTGGTATTGGGGGCG








CAGGCGCCGGGGTG







TNFRSF1A_P678__F
TNFRSF1A
NM_001065.2
23312372
GTCCCCCCACCCTGCCCCACTG
hypomethylation
72






TTGATCCTGGCTCTGCCACCAA








TCATG[CG]ACATCAGGCAACT








CCTCTCCTAAGCCTCTGTTGGT








TCCTTGTTTATTAA







PTPN6_P282_R
PTPN6
NM_080548.2
34328901
AGGAACTGGGCTGTTAGGGATT
hypomethylation
73






TTCCTTAGGCCCTTTGGTTTCC








GCCTA[CG]GAGAGGTTTCCCC








CATTGGTTGCTCTTCCTCAGCC








AGGGTTACTTCCTG







TM7SF3_P1068_R
TM7SF3
NM_016551.1
7706574
ACCACTGCAACTGGGTCTTGCA
hypomethylation
74






GTGGGGAAGAGGGACTGGGCTC








AACTC[CG]AATACAGCGTGGG








CAAGAGGGAATTTATAGCCAAC








CAGCAGTATGGAGT







KRT1_P798_R
KRT1
NM_006121.2
17318568
GGATAGCATGCAAACGCCCTTG
hypermethylation
75






AGTGAAAAAGCCCACAGAGCAG








TGAGA[CG]AGTAAATAGAAGC








TCTAGGACATTTTGTAAAGCAC








AGGGGTGGAGGTGA







IFNG E293_F
IFNG
NM_000619.2
56786137
AATGACTGCCTACAAGAGATGA
hypermethylation
76






CAGCCTATCAGAGATGCTACAG








CAAGT[CG]ATATTCAGTCATT








TTCAACCACAAACAAGTACTAT








TAAAAAGTCATACT







IFNG_P459_R
IFNG
NM_000619.2
56786137
AGCCTTTTAAAATTTTTCTTGC
hypermethylation
77






AAATGACCAGAAAGCAAGGAAA








GAATG[CG]GTTAAAAGAACAA








TTTGGTGAGGAAGTCCTTCATC








AGAGTTGGTTAGTA







MMP14_P13_F
MMP14
NM_004995.2
13027797
CGGGGACGGAGGAGAGGCTGTG
hypomethylation
78






GGAGAAGGGAGGGACCAGAGGA








GAGAG[CG]AGAGAGGGAACCA








GACCCCAGTTCGCCGACTAAGC








AGAAGAAAGATCAA







BCL2L2_P280_F
BCL2L2
NM_004050.2
14574571
CCAGGCACACAGTTCAGGGCTG
hypomethylation
79






GAAAAGTTCAACAAGTGCATGG








AACAT[CG]GAAACCTCCTGAA








AATGCTAAATTTGCCCCGAGAT








GTCCCGAAGTCCGG







CRIP1_P874_R
CRIP1
NM_001311.3
39725694
GCCTGGCACCGGGACCATCCTC
hypomethylation
80






CGCCTCAACTTTGCAGCGTACT








TGGAC[CG]CTCTGGCCGCCCT








GGGCGCTACCCGCAGAGATAAG








GGCCCCTCCCTGCG







APBA2_P227_F
APBA2
NM_005503.2
22035549
CCTTTGGAAATAAACACGAAGG
hypermethylation
81






TTCACTTGAAGACTTGGGGGAG








AATCA[CG]GTCAACTTGTGAC








GCTTGGTTTTTCAGATATTCAG








CTGCTCTGGAGAGC







CSF3R_P8_F
CSF3R
NM_172313.1
27437044
AGAAGTTCCTGAAACCAGCTGC
hypomethylation
82






AGTCCAGCTTCTCTCCCCGAGC








TCTGT[CG]TTAATGGCTCAGC








CTCTGACAGGCCCGGGGGCTGG








GGATTGCAACACCT







CARD15_P302_R
CARD15
NM_022162.1
11545911
TGGTGATGTAGCTGCTGGGAGG
hypomethylation
83






ACAGAGCTCCGAGTCACGTGGC








TTGGG[CG]GGCCTCCCCTTCC








TGGTGTCCACAGAAGCCCAACG








TCACTAGCTGGGGT







ALOX12_E85_R
ALOX12
NM_000697.1
4502050
GGCCGCTACCGCATCCGCGTGG
hypomethylation
84






CCACCGGGGCCTGGCTCTTCTC








CGGGT[CG]TACAACCGCGTGC








AGCTTTGGCTGGTCGGGACGCG








CGGGGAGGCGGAGC







MFAP4_P197_F
MFAP4
NM_002404.1
23111004
GGGAGGTGGGGCTGGAGCCAGG
hypomethylation
85






GGACCACCTGTGTCTCATTAGT








CCTGT[CG]GGCAAAGTACTGC








AGACGTTAACTCCCTGCTGGCT








CCAACTGTTCCCTG







GRB7_P160_R
GRB7
NM_001030002.1
71979666
CGGGACTCTTGATCTTCGCTCG
hypomethylation
86






TGGTACTGTCTGTTCGGCTGTC








TTCCC[CG]CCTCTCCCCAGGC








ACCTGCATCCTCCCTTGGCACC








TGCTGCCAGGCTAG







GRB7_E71_R
GRB7
NM_001030002.1
71979666
ATCTGGACACACAGGGCTCCCC
hypomethylation
87






CCCGCCTCTGACTTCTCTGTCC








GAAGT[CG]GGACACCCTCCTA








CCACCTGTAGAGAAGCGGGAGT








GGATCTGAAATAAA







CSF3_E242_R
CSF3
NM_172220.1
27437050
TGTCCCCGAGAGGGCCTCAGGT
hypomethylation
88






GGTAGGGAACAGCATGTCTCCT








GAGCC[CG]CTCTGTCCCCAGC








CCTGCAGCTGCTGCTGTGGCAC








AGTGCACTCTGGAC







RARA_P1076_R
RARA
NM_000964.2
75812906
GTCTTCTCCCCTTCTAGGGAGA
hypomethylation
89






GGCCATGCCCTCTCCCCTCAAG








TCTGT[CG]CTGACTTCCTCTG








GCCCTTCCCCTCATGACGTTTT








CCCTGCTCTGCTGC







STAT5A _P704_R
STAT5A
NM_003152.2
21618341
ACCCAAATGTGGCAATGGGTTT
hypomethylation
90






GTATCCAGCCACCGACAGGCTG








CATGA[CG]GTGGCAAAGTCAC








TTCCCCTCTCTGGCCTTTGTTT








TTCCACTTGTAAAA







CSF3R_P472_F
CSF3R
NM_172313.1
27437044
GGTTCCAGGGAATTGTGTAACC
hypomethylation
91






CAATACTCACTGCTCCCCTCTT








CATTA[CG]TATTCTGTGCATT








GCCCATAGACCAGGCAGATGGA








GAAACAGGAATTCT







PECAM1__E32_R
PECAM1
NM_000442.2
21314616
AAATTGCTCTGGTCACTTCTCC
hypomethylation
92






CGGCGCCTGCAGAGAGACCGGC








TGTGG[CG]CTGGTCAGGTAAT








GGCAGCCATGGCTGGAAACCGG








GAACAATGGGGCCT







PECAM1_P135_F
PECAM1
NM_000442.2
21314616
GTTTAGTTTCTTTAGGGAAAAA
hypomethylation
93






ACAAGGCACAAGTGACATTTGC








CTTGG[CG]TTCTTGACCCTCC








CTCTGTCTCGCCTGGGTTTGGG








GGCCCTTCTCATGG







SEPT9_P374_F
SEPT9.
NM_006640.2
19923366
TGGGGTACAGGGTGAAGAAGGG
hypomethylation
94






CTGGGGCCAGCCCAGGACAGAG








GAAGG[CG]AGGCAGGCACGCA








GGAACTGGGCTTTTTAAACCCT








TAAGCCCAAGGAAA







MATK_P190_R
MATK
NM_139355.1
21450845
GGGTGGGAGGCTTCCGAGAGCC
hypomethylation
95






GCCTCTCCCGGGGCATAAGGAA








GGAAG[CG]GGGCTGCAGGTAC








CGCCTGGGGTTCACAGCAGGGG








ACGAGGTGCCTCCC







EMR3_E61_F
EMR3
NM_152939.1
23397638
AGCTGACTCATGAAATTGCTAT
hypomethylation
96






CAGAAAAGCAAACTGCTTCCCC








TCTTT[CG]CCATCAGACTCAT








GGTTCTGCTTTTCGTTTATTTG








CTGTACCTTTTCTG











Any appropriate method can be used to obtain a blood sample that can be processed to obtain nucleic acid for the assessment of the human's CpG methylation site profile. For example, leukocyte nucleic acid can be obtained and assessed as described herein to determine whether any one or more of the methylation CpG sites listed in Table 1 or 5 have an altered level of methylation as compared to controls (e.g., healthy humans known to not have pancreatic cancer). In some cases, combinations of methylation CpG sites can be assessed as described herein. Examples of such combinations include, without limitation, (a) IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817; (b) LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817; (c) IL10_P348, ZAP70_P220, AIM2_P624, and TAL1_P817; (d) IL10_P348, LCN2_P86, AIM2_P624, and TAL1_P817; (e) IL10_P348, LCN2_P86, ZAP70_P220, and TAL1_P817; (f) IL10_P348, LCN2_P86, ZAP70_P220, and AIM2_P624; (g) IL10_P348, LCN2_P86, and ZAP70_P220; (h) IL10_P348, LCN2_P86, and AIM2_P624; (i) IL10_P348, LCN2_P86, and TAL1_P817; (j) IL10_P348, ZAP70_P220, and AIM2_P624; (k) IL10_P348, ZAP70_P220, and TAL1_P817; (l) IL10_P348, AIM2_P624, and TAL1_P817; (m) LCN2_P86, ZAP70_P220, and AIM2_P624; (n) LCN2_P86, ZAP70_P220, and TAL1_P817; (o) LCN2_P86, AIM2_P624, and TAL1_P817; (p) ZAP70_P220, AIM2_P624, and TAL1_P817; (q) IL10_P348 and LCN2_P86; (r) IL10_P348 and ZAP70_P220; (s) IL10_P348 and AIM2_P624; (t) IL10_P348 and TAL1_P817; (u) LCN2_P86 and ZAP70_P220; (v) LCN2_P86 and AIM2_P624; (w) LCN2_P86 and TAL1_P817; (x) ZAP70_P220 and AIM2_P624; (y) ZAP70_P220 and TAL1_P817; and (z) AIM2_P624 and TAL1_P817.


Any appropriate method can be used to assess a methylation CpG site for methylation level change (e.g., the presence or absence of a methyl group). For example, methylation assays available commercially (e.g., from Illumina) can be used to determine the methylation state of methylation CpG sites.


Once a human is determined to having altered levels of methylation of methylation CpG sites that are indicative of pancreatic cancer, then the human can be classified as having pancreatic cancer or can be evaluated further to confirm a diagnosis of pancreatic cancer. Humans identified as having pancreatic cancer as described herein can be treated with any appropriate pancreatic cancer treatment including, without limitation, surgery, radiation, and chemotherapy.


The invention will be further described in the following examples, which do not limit the scope of the invention described in the claims.


EXAMPLES
Example 1
Leukocyte DNA Methylation Signature Differentiates Pancreatic Cancer Patients from Healthy Controls
Study Population

PaC index cases were adult patients with a histologically confirmed primary adenocarcinoma of the pancreas seen at Mayo Clinic. Eligible Mayo pancreatic adenocarcinoma cases were identified through an ultra-rapid patient identification system and recruited into a prospective research registry. Study coordinators identified potential patients from the electronic patient scheduling system and daily pathology reports. All eligible patients were contacted either in the clinic at the time of their appointment, or later by mail or phone if clinic contact was not possible. If contacted at the clinic, a study coordinator obtained informed consent, arranged a venipuncture for 40 mL of blood prior to start of treatment (whenever possible), and asked the participant to complete the study questionnaire. If mail contact was required (approximately 28% of the cases were approached by mail), the study coordinator mailed an invitation letter to the patient's home address. A follow-up telephone call was made if the sample or forms were not received after one month. About 74% of all eligible patients were enrolled into the registry. From the registry, 132 never-smoker patients in phase I and 240 patients in phase II were selected with equal representation of sex, smoking status (smoker/nonsmoker) and stage of PaC (resectable, locally advanced and metastatic).


The healthy Caucasian controls were selected from a Mayo Clinic—based research registry of primary care control patients having routine check-up visits (general medical exam). Controls were frequency-matched to cases on age (±5 years), sex, and state/region of residence distribution of the cases. Controls had no previous diagnosis of cancer (except non-melanoma skin cancer) at the time of enrollment. Prior to their appointment, potential controls were mailed an information brochure describing the study and a letter of invitation. On the day of the appointment, a study assistant approached the subject, confirmed eligibility criteria, and obtained informed consent. Each participant completed study questionnaires (which included a self-report of height, weight, and diabetes status) and provided 30 mL of research blood sample. About 70% of all approached controls participated in this study. From this registry, 60 never smoker controls for phase I and 240 controls (half are never smokers) for phase II were selected.


DNA Modification by Sodium Bisulfite

DNA was extracted from 5 mL of whole blood utilizing an AutoGen FlexStar (AutoGen, Inc., Mass.), and the genomic DNA specimens were modified using the EZ DNA Methylation kit from Zymo Research Corporation (Orange, Calif.) that combined bisulfite conversion and DNA cleaning. The kit is based on the three-step reaction that takes place between cytosine and sodium bisulfite where cytosine is converted into uracil. 1 μg of genomic DNA from peripheral blood DNA was used for the modification per manufacturer recommendation. Treated DNA specimens were stored at −20° C. and were assayed within two weeks.


DNA Methylation Profiling Analysis

The Illumina (San Diego, Calif.) GoldenGate methylation Beadchip (cancer panel) and Illumina custom VeraCode methylation assay were used for phase I and phase II, respectively, following the manufacturer's procedure. The arrays were imaged using a BeadArray Reader scanner (Illumina, Inc.). The proportion methylated (β-value) at each CpG site was calculated using BeadStudio Software (Illumina, Inc.) after subtracting background intensity, which was computed from negative controls, from each analytical data point. The β-value represented relative ratio of fluorescent signals between the M (methylated) allele and M+U (unmethylated) alleles. This value ranges continuously from 0 (unmethylated) to 1 (fully methylated).


Differential Methylation Analysis

Due to non-Gaussian distribution of the CpG methylation values, Wilcoxon Rank Sum tests were used to examine differences in median β-values between cases and controls in both phase I and phase II. To correct for multiple testing in phase I, q-values were used to represent the false discovery rate (FDR) (Storey and Tibshirani, Proc. Natl. Acad. Sci. USA, 100(16):9440-5 (2003)). The CpGs with a FDR q-value≦0.05 level were considered significant. These CpGs were then candidates for phase II validation, where a p-value≦0.05 was considered significant. Bland-Altman plots were used to evaluate agreement between the two methylation assays in the 40 subjects assayed in both phase I and phase II. These plots allow evaluation of assay disagreement as a function of level of methylation (Bland and Altman, Lancet, 1(8476):307-10 (1986)).


Prediction Model Building

To develop prediction models, likelihood cross-validated penalized logistic regression models, which implemented either an L1 penalty (Lasso) (Tibshirani, J. Royal Statist. Soc. B, 58(1):267-88 (1996)) or an L2 penalty (Ridge) using the R package ‘penalized,’ were used (Goeman, Biometrical Journal, 52(1):70-84 (2010)). A Lasso model (or L1 penalty) was utilized in phase I testing study because of its desirable feature for model selection, which has a minimal effect on associated CpG coefficients while setting the unassociated CpGs' coefficients to zero. A Ridge regression model (or L2 penalty) that shrinks all coefficients to small values but not zeros was also considered for model building. The variable selection process is governed by a parameter that forces all coefficients to be shrunk near zero initially, then is gradually released to reduce the amount of shrinkage. The optimal value of this parameter is determined via cross validation. The Ridge model results were also compared to results from the Lasso model to hone the final model.


The final model identified through the penalized approaches was then fit as a generalized linear model (logistic regression) using the R package ‘glm’, in order to estimate the area under (AUC) the receiver operating characteristic (ROC) curve for each model. Models were fitted in both the testing set (phase I) and the validation set (phase II) separately with AUC reported for each model. In addition to the unadjusted model (only the CpGs), two more models were fitted, one that considered age, sex, and first degree family history as covariates and another that also considered ABO blood type (‘O’ vs ‘non-O’) as an additional covariate. ABO blood types were derived for a subset of patients which had GWAS genotype information (Petersen et al., Nat. Genet., 42(3):224-8 (2010)) available. The phase II models were fit two ways. First, coefficients from phase I were held fixed and discrimination assessed. Second, since the assay platform changed from phase I to phase II, the models were fit allowing the coefficients to be re-estimated.


Identification of Differentially Methylated CpG Sites in Phase I

For phase I, 132 never-smoker patients with PaC and 60 never-smoker healthy controls were examined. Due to chemo- or radiation therapy before blood was drawn, 13 patients were excluded from this analysis. The methylation status (β values) of 1,505 CpG sites from leukocyte DNAs in the remaining 119 cases and 60 controls were evaluated (Table 2). Because significant methylation differences on the X chromosome exist between males and females, CpG sites on autosomes and sex chromosome were analyzed separately. These analyses identified significant differences at 110 CpG sites in 92 independent genes (FDR≦0.05). 109 of the 110 significant CpG sites were located on autosomes. Table 3 lists the 10 most significant CpG sites in the phase I study.









TABLE 2







Subject demographics for Phases I and II.










Phase I
Phase II














Controls
Cases
P-
Controls
Cases
P-


Variable
(N = 60)
(N = 119)
value
(N = 215)
(N = 173)
value




















Age




1.00




1.00


≦49
3
(5%)
5
(4%)

20
(9%)
15
(9%)


50-54
4
(7%)
8
(7%)

14
(7%)
10
(6%)


55-59
7
(12%)
12
(10%)

28
(13%)
21
(12%)


60-64
7
(12%)
12
(10%)

33
(15%)
26
(15%)


65-69
12
(20%)
25
(21%)

39
(18%)
33
(19%)


70-74
11
(18%)
22
(18%)

32
(15%)
22
(13%)


75-79
11
(18%)
22
(18%)

29
(13%)
29
(17%)


80-84
3
(5%)
8
(7%)

16
(7%)
14
(8%)


≧85
2
(3%)
5
(4%)

4
(2%)
3
(2%)


Sex




0.87




0.90


Female
31
(52%)
60
(50%)

108
(50%)
88
(51%)


Male
29
(48%)
59
(50%)

107
(50%)
85
(49%)


Family History of


Pancreas Cancer


(1st degree)


No
58
(97%)
104
(87%)
0.046
196
(91%)
147
(85%)
0.06


Yes
2
(3%)
15
(13%)

19
(9%)
26
(15%)


Smoking Status









0.90


Never Smokers
60
(100%)
119
(100%)

97
(45%)
77
(45%)


Ever Smokers
0

0


118
(55%)
96
(55%)


Stage of Pancreas


Cancer


Resectable


31
(26%)



58
(34%)


Locally


45
(38%)



59
(34%)


Advanced


Metastatic


43
(36%)



56
(32%)


GWAS




<0.001




0.028


genotyping


No
34
(57%)
32
(27%)

106
(49%)
66
(38%)


Yes
26
(43%)
87
(73%)

109
(51%)
107
(62%)
















TABLE 3







Top 10 most differentially methylated CpG sites


in phase I and validation in phase II.












Median β
Median
Difference



Illumina ID
Control
β Case
(case-control)
p value












Phase I











ITK_P114_F
0.8337
0.9006
0.0669

<1E−10



LCN2_P86_R
0.5608
0.4398
−0.121
2.00E−10


ITK_E166_R
0.8859
0.9414
0.0555
5.00E−10


PECAM1_E32_R
0.2319
0.1566
−0.0753
1.60E−09


LMO2_E148_F
0.3885
0.2704
−0.1181
2.30E−09


IL10_P348_F
0.6026
0.4597
−0.1429
2.50E−09


LCK_E28_F
0.8114
0.8684
0.057
3.60E−09


RUNX3_P247_F
0.7837
0.8672
0.0835
5.90E−09


LMO2_P794_R
0.3143
0.2027
−0.1116
1.02E−08


MMP14_P13_F
0.4721
0.3472
−0.1249
2.27E−08









Phase II











ITK_P114_F
0.846
0.8898
0.0438

<1E−10



LCN2_P86_R
0.591
0.4993
−0.0917

<1E−10



ITK_E166_R
0.8885
0.9299
0.0414

<1E−10



PECAM1_E32_R
0.2851
0.2211
−0.064

<1E−10



LMO2_E148_F
0.4969
0.3904
−0.1065

<1E−10



IL10_P348_F
0.7191
0.6382
−0.0809

<1E−10



LCK_E28_F
0.8593
0.8999
0.0406

<1E−10



RUNX3_P247_F
0.7528
0.841
0.0882

<1E−10



LMO2_P794_R
0.3754
0.3027
−0.0727
6.00E−10


MMP14_P13_F
0.5694
0.4807
−0.0887

<1E−10










To evaluate possible methylation changes during tumor progression, the methylation differences among three stages of PaC within this patient population, including 31 resectable, 45 locally advanced, and 43 metastatic cases, were examined. Although nine CpG sites showed a trend in association with clinical stages (p<0.01) (Table 4), the data analysis did not reveal significant difference among the three stages (all CpG sites with FDR>0.05).









TABLE 4







Top 10 most differentially methylated CpG sites among 3 clinical stages.










Mean β values















Gene

Locally

p



Illumina ID
Name
Resectable
Advanced
Metastatic
value
FDR





ZMYND10_P329_F
ZMYND10
0.045
0.032
0.019
0.001
0.722


EPO_P162_R
EPO
0.077
0.046
0.068
0.001
0.722


SCGB3A1_P103_R
SCGB3A1
0.004
0.020
0.004
0.002
0.722


MEST_P4_F
MEST
0.042
0.029
0.061
0.002
0.722


PWCR1_P357_F
PWCR1
0.917
0.920
0.890
0.003
0.722


NTRK3_P636_R
NTRK3
0.009
0.009
0.004
0.003
0.722


TIE1_E66_R
TIE1
0.203
0.161
0.153
0.006
1.000


HLA_DPA1_P205_R
HLA
0.065
0.041
0.052
0.007
1.000


EDNRB_P148_R
EDNRB
0.995
0.995
0.995
0.009
1.000


COL1A2_P48_R
COL1A2
0.033
0.023
0.028
0.011
1.000









Validation of Selected CpG Sites in Phase II

To validate the differentially methylated CpG sites identified in phase I within a larger number of patients and a broader range of demographic characteristics, a custom VeraCode methylation assay (Illumina, Inc.) was designed, and 96 of the 110 significant CpG sites were examined in 240 PaC cases and 240 matched controls. The 96 CpG sites were selected according to FDR values and median differences between cases and controls. Among the 480 subjects, 40 phase I subjects (20 cases and 20 controls) were included in order to compare the degree of agreement between the two methylation assays. Bland Altman plots (Bland and Altman, Lancet, 1(8476):307-10 (1986)) showed little mean shift and constant variation of differences over the range of values (FIG. 1), demonstrating reasonable agreement between the two assays. The two assays were significantly correlated as expected among all 96 CpG sites (mean Spearman correlation coefficient r=0.95).


Among the 220 PaC patients who were unique to phase II, 47 patients were treated before blood was drawn. The methylation levels between these 47 treated cases and 173 never-treated cases were compared to evaluate the effect of treatment on the methylation status of these selected CpG sites. Two CpG sites (TAL1_P817 F and CSF3_E242_R) exhibited nominal differences (p=0.001 and 0.025, respectively), although these results could be due to chance, given the large number of comparisons. Overall, a significant treatment effect on the methylation of these selected CpG sites was not observed. Similarly, no effect was attributable to smoking history. Of the remaining 220 controls, five additional controls were excluded due to inadequate quality, leaving 215 controls who were unique to phase II (Table 2). A total of 173 never-treated cases and 215 controls were used for analysis in phase II. The Wilcoxon Rank Sum Test identified a significant difference (p<0.05) in 88 of the 96 selected CpGs. Importantly, all 88 of these validated CpG sites in phase II also exhibited the same direction of methylation change as phase I (FIG. 2). Of those, 23 and 65 CpG sites demonstrated hypermethylation and hypomethylation in PaC patients, respectively. Table 3 lists the 10 most significant CpG sites in the phase II study (Table 5 contained statistics of the 96 CpG sites in both phases I and II).









TABLE 5







Summary statistics (median (min, max) of the 96 significantly differentially


methylated CpG sites by phase and case/control status.










CpG
Controls
Cases
p-value*












Phase I










ITK_P114_F
83.37 (66.78, 92.51)
90.06 (48.41, 97.28)

<1E−10



LCN2_P86_R
56.08 (32.4, 78.23) 
43.98 (5.71, 92.14) 
2.00E−10


ITK_E166_R
88.59 (71.81, 96.04)
94.14 (50.72, 99.63)
5.00E−10


PECAM1_E32_R
23.19 (12.47, 45.11)
15.66 (1.16, 44.89) 
1.60E−09


LMO2_E148_F
38.85 (13.84, 64.09)
27.04 (3.69, 77.03) 
2.30E−09


IL10_P348_F
60.26 (31.16, 79.7) 
45.97 (1.14, 88.97) 
2.50E−09


LCK_E28_F
81.14 (65.35, 90.81)
86.84 (50.58, 96.12)
3.60E−09


RUNX3_P247_F
78.37 (41.19, 91.2) 
86.72 (32.49, 96.71)
5.90E−09


LMO2_P794_R
31.43 (10.99, 54.48)
20.27 (0.43, 70.88) 
1.02E−08


MMP14_P13_F
47.21 (23.97, 77.03)
34.72 (0.95, 81.85) 
2.27E−08


CTLA4_E176_R
90.98 (76.72, 97.1) 
94.27 (73.46, 99.51)
2.43E−08


SPI1_P48_F
 39.1 (13.89, 63.67)
28.97 (0.46, 75.52) 
3.00E−08


SLC22A18_P216_R
 35.3 (15.09, 60.06)
24.88 (2.89, 71.26) 
3.22E−08


RUNX3_P393_R
82.38 (49.34, 92.26)
88.77 (39.04, 97.27)
3.27E−08


TRIP6_P1090_F
30.42 (8.07, 66.9) 
22.32 (3.25, 74.23) 
4.17E−08


RARA_P1076_R
22.76 (10.53, 47.06)
16.02 (1.68, 48.24) 
8.70E−08


PI3_P274_R
75.78 (53.4, 91.48) 
65.96 (10.63, 95.55)
8.85E−08


ERCC3_P1210_R
61.67 (38.27, 80.11)
50.39 (18.34, 89.01)
9.79E−08


LCN2_P141_R
72.86 (42.33, 87.3) 
64.16 (22.65, 94.55)
1.16E−07


RUNX3_E27_R
89.46 (71.07, 98.1) 
93.35 (11.97, 99.64)
1.87E−07


TNFRSF1A_P678_F
65.33 (47.4, 79.92) 
56.61 (23.05, 87.1) 
2.14E−07


GFI1_P208_R
19.6 (4.31, 46.99)
12.75 (0, 36.77)   
2.28E−07


CD9_P585_R
33.34 (13.45, 50.34)
26.51 (5.27, 56.39) 
2.32E−07


MFAP4_P197_F
22.82 (6.75, 55.77) 
16.41 (2.01, 56.84) 
2.96E−07


AIM2_P624_F
37.67 (17.86, 58.1) 
28.43 (2.03, 61.51) 
3.54E−07


TRIP6_P1274_R
43.57 (14.61, 74.3) 
32.95 (0.76, 76.92) 
5.36E−07


CSF3R_P472_F
33.44 (15.09, 55.24)
23.61 (0.68, 69.4) 
6.91E−07


ZAP70_P220_R
28.41 (0.19, 47.82) 
35.31 (0, 59.95)   
8.47E−07


GRB7_E71_R
29.92 (11.39, 58.66)
22.23 (5.27, 84.04) 
1.55E−06


IFNG_E293_F
76.11 (44.81, 90.56)
82.66 (40.37, 99.16)
1.57E−06


LTA_P214_R
79.91 (61.63, 93.55)
85.5 (44.8, 94.89)
2.13E−06


SEPT9_P374_F
24.56 (11.19, 48.39)
17.19 (2.52, 59.09) 
2.55E−06


CD9_P504_F
13.81 (1.88, 28.33) 
8.02 (0.54, 39.44)
3.19E−06


SPI1_E205_F
20.85 (1.87, 42.24) 
15.34 (1.34, 49.21) 
4.34E−06


ZMYND10_P329_F
4.65 (0, 21)    
2.35 (0, 18.04)  
4.53E−06


CSF3R_P8_F
20.73 (1.86, 41.89) 
14.64 (0.77, 42.8) 
4.54E−06


CSF3_E242_R
66.58 (49.37, 81.52)
59.27 (21.44, 90.38)
5.10E−06


PECAM1_P135_F
18.55 (0.47, 45.36) 
11.37 (0.19, 33.84) 
5.10E−06


EMR3_E61_F
15.65 (5.25, 34.99) 
11.63 (0.24, 41.7) 
6.43E−06


STAT5A_P704_R
16.81 (5.15, 46.21) 
12.17 (0.28, 41.17) 
6.52E−06


MMP9_P189_F
31.53 (1.9, 56.05) 
22.65 (0.4, 49.69) 
7.01E−06


SLC5A5_E60_F
45.17 (21.04, 74.82)
37.67 (8.07, 76.8) 
8.56E−06


CRIP1_P874_R
13.49 (4.42, 29.09) 
10.29 (1.06, 25.26) 
1.33E−05


SYK_P584_F
38.57 (0.24, 59.13) 
30.97 (0.67, 68.67) 
1.34E−05


APBA2_P227_F
94.88 (84.03, 99.63)
97.09 (84.71, 99.65)
1.38E−05


TM7SF3_P1068_R
56.68 (23.59, 82.45)
46.79 (16.31, 87.94)
1.59E−05


RAB32_E314_R
1.98 (0.27, 11.26)
0.91 (0, 9.5)   
1.72E−05


TAL1_P817_F
21.45 (0, 49.38)   
14.26 (0, 40.73)   
1.74E−05


IGFBP5_P9_R
12.66 (0.07, 29.2) 
8.85 (0, 27.87)  
1.90E−05


HPN_P374_R
9.66 (0.26, 23.76)
7.17 (0, 26.79)  
2.53E−05


RHOH_P953_R
97.62 (72.16, 99.47)
99.03 (76.43, 99.6) 
3.49E−05


MPL_P62_F
29.8 (2.41, 58.43)
22.88 (0, 55.22)   
3.54E−05


PADI4_E24_F
17.86 (0.32, 38.35) 
11.31 (0, 41.96)   
3.83E−05


AIM2_E208_F
 96.3 (80.67, 99.46)
97.97 (80.23, 99.54)
4.20E−05


KRT1_P798_R
83.01 (66.54, 93.3) 
85.93 (68.78, 93.73)
4.20E−05


GPR116_P850_F
96.05 (89.31, 98.99)
97.09 (90.05, 99.25)
4.26E−05


TIE1_E66_R
21.18 (0.91, 42.26) 
15.33 (0.55, 51.7) 
4.79E−05


HGF_E102_R
19.94 (7.37, 42.41) 
15.13 (0.53, 50.53) 
5.46E−05


PADI4_P1011_R
 69.9 (51.57, 81.11)
73.91 (51.55, 88.23)
5.53E−05


GSTM2_P453_R
59.15 (40.51, 83.4) 
53.81 (25.36, 79.44)
6.80E−05


NOTCH4_E4_F
15.25 (1.14, 41.15) 
9.84 (0.61, 35.21)
6.89E−05


MMP8_E89_R
64.58 (42.74, 83.76)
55.81 (0, 85.68)   
7.64E−05


HIC_1_sEq_48_S103_R
27.61 (0.09, 70.36) 
19.73 (0, 80.7)   
9.84E−05


IFNG_P459_R
85.46 (65.44, 97.27)
88.28 (53.34, 96.99)
1.06E−04


EPHA2_P203_F
43.85 (25.91, 67.36)
36.39 (6.07, 77.13) 
1.07E−04


CD82_P557_R
19.56 (0, 51.55)   
13.07 (0, 43.55)   
1.08E−04


VAMP8_P241_F
31.69 (11.54, 50.58)
24.36 (0.94, 54.16) 
1.25E−04


CD86_P3_F
12.46 (0.32, 40.34) 
9.46 (0.29, 32.83)
1.72E−04


DHCR24_P652_R
44.87 (14.92, 62.58)
  39 (14.67, 66.69)
1.76E−04


SPARC_P195_F
14.27 (2.87, 32.85) 
11.31 (0.52, 39.17) 
1.83E−04


IL1RN_P93_R
 94.2 (87.08, 99.47)
95.59 (85.25, 99.49)
2.17E−04


IFNGR2_P377_R
21.62 (7.95, 48.7) 
16.2 (0, 68.34)  
2.17E−04


CARD15_P302_R
9.02 (0.6, 28.97) 
5.96 (0, 27.3)   
2.69E−04


BCL2L2_P280_F
7.89 (0, 21.29)  
4.95 (0, 25.19)  
2.78E−04


SLC22A18_P472_R
83.47 (72.01, 94.27)
80.33 (34.95, 93.43)
3.56E−04


CSF1R_E26_F
66.55 (30.32, 88.93)
58.76 (16.56, 86.36)
4.34E−04


CLDN4_P1120_R
89.62 (78.16, 96.19)
91.19 (76.74, 97.54)
4.54E−04


GRB7_P160_R
60.07 (33.43, 80.13)
51.85 (14.14, 95.94)
6.39E−04


AXL_E61_F
7.82 (0, 23.86)  
5.17 (0, 42)    
7.93E−04


ALOX12_E85_R
47.85 (7.84, 90.76) 
37.95 (2.82, 84.99) 
7.98E−04


TFPI2_P152_R
8.68 (1.16, 25.69)
7.23 (0, 19.55)  
8.43E−04


AGXT_P180_F
84.04 (54.05, 94.35)
78.61 (30.32, 95.02)
8.90E−04


IL10_P85_F
16.33 (2.21, 31.74) 
11.98 (0.6, 28.58) 
1.04E−03


KCNK4_E3_F
30.96 (16.67, 58.04)
26.78 (12.25, 65.38)
1.16E−03


JAK3_P1075_R
69.62 (43.74, 86.14)
64.45 (39.85, 85.81)
1.31E−03


IL6_P213_R
4.39 (0.3, 16.26) 
3.24 (0, 12.35)  
1.36E−03


NOTCH4_P938_F
77.66 (57.82, 90.79)
 80.6 (58.86, 92.06)
1.36E−03


PTPN6_P282_R
17.03 (0, 39.81)   
12.82 (0, 52.14)   
1.39E−03


MATK_P190_R
10.43 (0.92, 26.11) 
6.55 (0, 40.44)  
1.52E−03


CEACAM1_P44_R
7.92 (2.35, 21.58)
5.91 (0.12, 17.51)
1.62E−03


CASP10_P334_F
12.55 (0.26, 42.94) 
9.29 (0, 39.33)  
1.66E−03


FGF1_P357_R
95.37 (87.76, 99.49)
96.51 (86.05, 99.63)
2.14E−03


IL17RB_E164_R
10.41 (0.69, 28.02) 
7.84 (0, 29.55)  
2.21E−03


CPA4_E20_F
 83.5 (64.39, 93.13)
86.45 (59.8, 99.29) 
2.28E−03


PTHR1_P258_F
62.11 (31.07, 81.92)
66.79 (38.33, 85.98)
2.50E−03


ESR1_P151_R
9.47 (0.17, 28.16)
7.72 (0, 26.14)  
3.44E−03









Phase II










ITK_P114_F
84.6 (4.07, 94.97)
88.98 (65.48, 95.66)

<1E−10



LCN2_P86_R
 59.1 (25.07, 89.12)
49.93 (13.42, 87.19)

<1E−10



ITK_E166_R
88.85 (75.13, 97.07)
92.99 (66.52, 97.68)

<1E−10



PECAM1_E32_R
28.51 (3.17, 58.59) 
22.11 (7.07, 47.24) 

<1E−10



LMO2_E148_F
49.69 (12.63, 66.96)
39.04 (9.57, 74.81) 

<1E−10



IL10_P348_F
71.91 (30.76, 84.99)
63.82 (18.98, 86.99)

<1E−10



LCK_E28_F
85.93 (66.63, 94.24)
89.99 (69.32, 95.97)

<1E−10



RUNX3_P247_F
75.28 (46.66, 92.97)
84.1 (44.68, 94.7)

<1E−10



LMO2_P794_R
37.54 (7.76, 66)   
30.27 (4.33, 67.54) 
6.00E−10


MMP14_P13_F
56.94 (1.91, 75.33) 
48.07 (14.03, 82.2) 

<1E−10



CTLA4_E176_R
90.42 (70.84, 96.69)
93.6 (75.8, 97.07)

<1E−10



SPI1_P48_F
0 (0, 65.26)
0 (0, 66.39)
8.73E−01


SLC22A18_P216_R
45.39 (3.56, 67.22) 
37.63 (11.09, 65.12)

<1E−10



RUNX3_P393_R
85.91 (60.74, 94.14)
90.52 (59.59, 96.07)

<1E−10



TRIP6_P1090_F
49.69 (15.94, 78.31)
42.87 (7.49, 71.8) 
7.20E−09


RARA_P1076_R
15.22 (2.19, 34.67) 
10.9 (2.49, 31.5) 

<1E−10



PI3_P274_R
76.46 (11.61, 86.93)
68.74 (33.03, 89.85)

<1E−10



ERCC3_P1210_R
63.04 (34.49, 76.41)
53.35 (20.9, 81.21) 

<1E−10



LCN2_P141_R
70.29 (6.04, 90.27) 
63.03 (26.51, 90.6) 

<1E−10



RUNX3_E27_R
85.68 (59.92, 96.29)
90.88 (64.9, 97.41) 

<1E−10



TNFRSF1A_P678_F
69.85 (28.76, 83.56)
62.92 (32.87, 84.15)

<1E−10



GFI1_P208_R
27.99 (2.92, 57.92) 
21.48 (2.67, 51.52) 

<1E−10



CD9_P585_R
29.61 (4.66, 54.39) 
25.49 (12.88, 46.71)

<1E−10



MFAP4_P197_F
20.52 (9.22, 37.18) 
15.63 (5.54, 32.33) 

<1E−10



AIM2_P624_F
24.47 (2.07, 47.94) 
18.36 (4.35, 43.95) 

<1E−10



TRIP6_P1274_R
0 (0, 74.89)
0 (0, 72.24)
1.19E−01


CSF3R_P472_F
35.13 (12.28, 53.48)
27.56 (6.94, 61.54) 

<1E−10



ZAP70_P220_R
47.65 (2.73, 76.92) 
52.39 (33.54, 75.02)
1.50E−09


GRB7_E71_R
36.02 (1.92, 61.12) 
29.79 (6.77, 62.93) 
 l.00E−09


IFNG_E293_F
70.66 (21.85, 87.7) 
77.72 (39.38, 91.66)

<1E−10



LTA_P214_R
81.58 (59.26, 94.06)
86.32 (57.97, 94.15)

<1E−10



SEPT9_P374_F
0 (0, 56.25)
0 (0, 58.96)
7.74E−02


CD9_P504_F
31.4 (1.94, 58.89)
23.61 (2.66, 54.55) 

<1E−10



SPI1_E205_F
46.01 (1.94, 68.8) 
38.93 (2.04, 67.89) 

<1E−10



ZMYND10_P329_F
8.93 (2.5, 36.09) 
7.42 (1.79, 27.24)
3.35E−07


CSF3R_P8_F
27.34 (3.84, 54.47) 
21.74 (5.7, 52.03) 

<1E−10



CSF3_E242_R
61.98 (40.79, 78.17)
56.43 (33.01, 78.13)

<1E−10



PECAM1_P135_F
14.99 (3.05, 32.67) 
11.05 (3.26, 25.28) 

<1E−10



EMR3_E61_F
20.71 (6.49, 38.41) 
15.09 (3.15, 38.97) 

<1E−10



STAT5A_P704_R
30.55 (3.94, 52.04) 
22.97 (6.02, 52.51) 

<1E−10



MMP9_P189_F
37.54 (3.11, 57.08) 
32.85 (7.59, 55.08) 
1.30E−09


SLC5A5_E60_F
51.28 (27.1, 74.6) 
47.82 (9.37, 68.78) 
7.29E−06


CRIP1_P874_R
20.02 (2.69, 42.34) 
17.73 (8.46, 34.07) 
2.48E−05


SYK_P584_F
44.33 (4.94, 64.17) 
37.47 (2.48, 68.35) 

<1E−10



APBA2_P227_F
92.19 (84.38, 97.59)
93.86 (74.03, 97.18)

<1E−10



TM7SF3_P1068_R
54.8 (24.74, 84.6)
46.58 (9.06, 71.14) 

<1E−10



RAB32_E314_R
3.97 (2.42, 15.73)
3.82 (2.18, 10.52)
5.02E−02


TAL1_P817_F
27.29 (5.59, 46.43) 
25.55 (9.32, 43.64) 
3.56E−02


IGFBP5_P9_R
21.5 (3.54, 43.93)
18.17 (3.12, 48.74) 
3.03E−07


HPN_P374_R
20.25 (5.94, 66.95) 
16.97 (7.79, 77.97) 
3.46E−07


RHOH_P953_R
92.75 (63.97, 96.75)
94.02 (77.66, 96.71)
2.00E−10


MPL_P62_F
34.54 (4.53, 66.72) 
28.09 (9.17, 53.73) 

<1E−10



PADI4_E24_F
24.96 (2.95, 47.22) 
20.03 (2.9, 47.69) 

<1E−10



AIM2_E208_F
94.45 (77.86, 97.47)
95.66 (83.76, 98.08)

<1E−10



KRT1_P798_R
 89.5 (71.75, 93.92)
91.48 (75.18, 94.92)

<1E−10



GPR116_P850_F
95.47 (90.14, 97.05)
96.11 (92.96, 97.1) 

<1E−10



TIE1_E66_R
29.29 (2.4, 51.91) 
23.94 (2.85, 47.27) 

<1E−10



HGF_E102_R
23.18 (1.86, 41.47) 
19.87 (2.6, 39.95) 
1.12E−06


PADI4_P1011_R
76.61 (9.64, 87.91) 
81.19 (55.69, 89.2) 

<1E−10



GSTM2_P453_R
64.77 (39.09, 86.35)
 62.7 (40.83, 76.29)
9.83E−03


NOTCH4_E4_F
20.61 (6.52, 44.05) 
16.87 (3.08, 33.64) 
6.00E−10


MMP8_E89_R
70.66 (6.82, 86.44) 
65.54 (32.82, 78.69)

<1E−10



HIC_l_sEq_48_S103_R
19.78 (7.67, 47.09) 
18.19 (3.33, 55.88) 
3.11E−02


IFNG_P459_R
89.86 (64.27, 96.86)
92.57 (66.81, 97.08)

<1E−10



EPHA2_P203_F
74.53 (3.66, 89.34) 
67.54 (30.76, 87.52)

<1E−10



CD82_P557_R

22 (2.73, 60.61)

17.48 (2.62, 39)   
5.40E−09


VAMP8_P241_F
40.17 (2.11, 63.54) 
34.37 (14.11, 52.08)

<1E−10



CD86_P3_F
15.87 (2.39, 30.32) 
13.49 (2.9, 28.27) 
2.22E−05


DHCR24_P652_R
48.39 (23.78, 74.34)
41.86 (17.02, 67.4) 

<1E−10



SPARC_P195_F
14.5 (3.93, 36.44)
13.39 (5.63, 37.38) 
7.57E−06


IL1RN_P93_R
 94.3 (85.78, 97.34)
95.28 (90.71, 97.45)

<1E−10



IFNGR2_P377_R

29 (2.85, 53.14)

22.53 (3.82, 41.23) 

<1E−10



CARD15_P302_R
19.22 (3.24, 45.09) 
14.16 (3.66, 36.68) 
5.70E−09


BCL2L2_P280_F
18.13 (2.77, 54.1) 
16.71 (2.46, 44.21) 
3.81E−03


SLC22A18_P472_R
 86.1 (69.16, 93.29)
84.96 (73.83, 91.2) 
6.48E−04


CSF1R_E26_F
74.92 (25.36, 90.91)
70.85 (39.78, 91.21)
3.45E−07


CLDN4_P1120_R
91.31 (73.07, 95.82)
92.64 (77.49, 95.59)

<1E−10



GRB7_P160_R
72.13 (41.09, 88.74)
71.11 (13.96, 92.63)
1.56E−01


AXL_E61_F
15.47 (2.5, 40.29) 
13.19 (3, 40.16)   
2.54E−03


ALOX12_E85_R
54.6 (6.87, 85.62)
51.44 (7.44, 88.52) 
6.15E−02


TFPI2_P152_R
13.78 (2.43, 29.91) 
13.21 (2.21, 29.07) 
1.97E−01


AGXT_P180_F
77.55 (44.53, 90.06)
74.85 (33.53, 87.81)
1.03E−03


IL10_P85_F
21.04 (2.06, 38.09) 
16.05 (5.04, 46.92) 

<1E−10



KCNK4_E3_F
0 (0, 89.11)
0 (0, 63.18)
7.74E−01


JAK3_P1075_R
70.21 (46.11, 85.05)
68.02 (43.53, 87.34)
5.43E−03


IL6_P213_R
10.48 (2.53, 33.05) 
7.87 (2.03, 25.36)
1.33E−08


NOTCH4_P938_F
77.74 (44, 87.97)  
82.18 (64.28, 89.48)

<1E−10



PTPN6_P282_R
23.29 (3.67, 71.66) 
18.9 (2.67, 72.99)
1.96E−05


MATK_P190_R
10.37 (3.76, 38.93) 
8.33 (2.91, 26.71)
1.35E−06


CEACAM1_P44_R
10.06 (3.35, 25.72) 
8.58 (2.81, 24.96)
4.35E−04


CASP10_P334_F
22.91 (10.21, 49.38)
21.77 (9.58, 47.71) 
2.88E−02


FGF1_P357_R
93.66 (77.45, 96.31)
94.92 (84.85, 97.12)

<1E−10



IL17RB_E164_R
11.97 (2.77, 43.06) 
12.35 (2.96, 37.44) 
7.60E−01


CPA4_E20_F
88.05 (56.56, 93.9) 
90.57 (68.86, 97.31)
1.00E−10


PTHR1_P258_F
64.33 (3.69, 83.88) 
68.73 (35.03, 83.62)
4.00E−10


ESR1_P151_R
10.92 (2.9, 25.71) 
8.85 (2.34, 24.42)
7.80E−09









Building and Validation of the Prediction Model

To build prediction models based on phase I data, 43 of the 96 CpG sites that showed less than 5% median β differences between cases and controls or p-value≧0.001 (FDR>0.007) in phase I were excluded. These filter criteria were set for the following technical considerations. First, CpG sites with smaller methylation differences are prone to laboratory error due to technical limitations. Second, CpG sites with less significant p-values are less likely to be replicated in future studies. Based on 53 remaining CpG sites, models were built using L1 and L2 penalties as described above using the phase I data.


An effective model was chosen based on criteria of ROC AUC and parsimony. This model was then tested using the phase II data without the 40 subjects assayed in both phases for the agreement study. When considering all cases and all controls, a panel of five CpG sites (Model I: IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817) was identified. These five CpG sites were the first five CpGs to enter and remain in the Lasso model and also had the five largest coefficients from the Ridge model. This five CpG-only model exhibited good discrimination between patients and controls (c-statistic=0.85 in phase I and 0.76 in phase II) based on the logistic regression model. When including covariates in the logistic regression model (age, sex, 1st degree of family history of PaC, and ABO blood type), the discrimination was improved in phase I (c-statistic=0.89), but decreased in phase II (c-statistic=0.72). When re-estimating coefficients in phase II (re-fitting), the discrimination was improved, but not dramatically (c-statistic=0.77 for five CpGs only, 0.77 after inclusion of covariates) (Table 6). When including resectable patients only and all controls, one CpG site (Model II: LCN2_P86) was identified that appeared to discriminate for resectable disease (c-statistic=0.78 in phase I and 0.74 in phase II).









TABLE 6







Methylation-based predication models and Area Under the ROC Curve (AUC).











Phase I
Phase II
Phase II - Re-fit





















CpG +


CpG +


CpG +


Mod-
CpG
CpGs
CpG +
Covariates* +
CpGs
CpG +
Covariates* +
CpGs
CpG +
Covariates* +


els
Illumina ID
only
Covariates*
ABO**
only
Covariates*
ABO**
only
Covariates*
ABO**













All Cases and All
60 controls, 119 cases
215 controls, 173 cases
215 controls, 173 cases


Controls

















I
IL10_P348
0.85
0.86
0.89
0.76
0.75
0.72
0.77
0.77
0.77



LCN2_P86



ZAP70_P220



AIM2_P624



TAL1_P817










Resectable Cases and
60 controls, 31 cases 
215 controls, 58 cases 
215 controls, 58 cases 


All Controls

















II
LCN2_P86
0.78
0.79
0.82
0.74
0.67
0.64
0.73
0.73
0.73





*Covariates includes age, sex, 1st degree Family history of PaC.


**ABO-blood type of O and non-O.






The results provided herein demonstrate that epigenetic variation in leukocyte DNA, manifested by reproducible methylation differences, can be used as an early diagnostic marker for differentiating between pancreatic cancer patients and humans without pancreatic cancer (e.g., healthy humans). For example, a panel that includes the IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites can be used to identify pancreatic cancer patients. The results provided herein also demonstrate that the LCN2_P86 CpG methylation site is capable of identifying human patients with resectable pancreatic cancer.


Other Embodiments

It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims
  • 1. A method for identifying a human as having pancreatic cancer, wherein said method comprises: (a) determining whether or not nucleic acid obtained from a blood sample of a human comprises at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer, wherein said at least three methylation CpG sites are selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites, and(b) classifying said human as having pancreatic cancer if said nucleic acid comprises said at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer, and classifying said human as not having pancreatic cancer if said nucleic acid does not comprise said at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer.
  • 2. The method of claim 1, wherein said blood sample is a blood sample obtained from a human not subjected to a prior pancreas tissue biopsy.
  • 3. The method of claim 1, wherein said method comprises determining whether or not nucleic acid obtained from said blood sample comprises at least four methylation CpG sites that have an altered methylation status indicative of pancreatic cancer.
  • 4. The method of claim 3, wherein said at least four methylation CpG sites are selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites.
  • 5. The method of claim 1, wherein said method comprises determining whether or not nucleic acid obtained from said blood sample comprises at least five methylation CpG sites that have an altered methylation status indicative of pancreatic cancer.
  • 6. The method of claim 5, wherein said at least five methylation CpG sites are selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites.
  • 7. A method for identifying a human as having pancreatic cancer, wherein said method comprises: (a) detecting the presence of at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer in nucleic acid obtained from a blood sample of a human, wherein said at least three methylation CpG sites are selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites, and(b) classifying said human as having pancreatic cancer based at least in part on the presence of said at least three methylation CpG sites that have an altered methylation status indicative of pancreatic cancer.
  • 8. The method of claim 7, wherein said blood sample is a blood sample obtained from a human not subjected to a prior pancreas tissue biopsy.
  • 9. The method of claim 7, wherein said method comprises detecting the presence of at least four methylation CpG sites that have an altered methylation status indicative of pancreatic cancer in said nucleic acid.
  • 10. The method of claim 9, wherein said at least four methylation CpG sites are selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites.
  • 11. The method of claim 7, wherein said method comprises detecting the presence of at least five methylation CpG sites that have an altered methylation status indicative of pancreatic cancer in said nucleic acid.
  • 12. The method of claim 11, wherein said at least five methylation CpG sites are selected from the group consisting of IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, and TAL1_P817 CpG methylation sites.
  • 13. A method for identifying a human as having resectable pancreatic cancer, wherein said method comprises: (a) determining whether or not nucleic acid obtained from a blood sample of a human comprises hypomethylation of an LCN2_P86 methylation CpG site, and(b) classifying said human as having resectable pancreatic cancer if said nucleic acid comprises said hypomethylation of said LCN2_P86 methylation CpG site, and classifying said human as not having resectable pancreatic cancer if said nucleic acid does not comprise said hypomethylation of said LCN2_P86 methylation CpG site.
  • 14. A method for identifying a human as having resectable pancreatic cancer, wherein said method comprises: (a) detecting hypomethylation of an LCN2_P86 methylation CpG site of nucleic acid obtained from a blood sample of a human, and(b) classifying said human as having resectable pancreatic cancer based at least in part on said hypomethylation.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application Serial No. 61/417,066, filed Nov. 24, 2010. The disclosure of the prior application is considered part of (and are incorporated by reference in) the disclosure of this application.

STATEMENT AS TO FEDERALLY SPONSORED RESEARCH

This invention was made with government support under grant CA102701 awarded by the National Institutes of Health. The government has certain rights in the invention.

PCT Information
Filing Document Filing Date Country Kind 371c Date
PCT/US11/61897 11/22/2011 WO 00 5/24/2013
Provisional Applications (1)
Number Date Country
61417066 Nov 2010 US