Early detection of pancreatic and periampullary neoplasms is critical to improve their clinical outcome. The present authors previously demonstrated that DNA hypermethylation of
Carcinoma of the exocrine pancreas or pancreatic cancer (PC) is one of the most aggressive solid tumors (
Early detection of PC is the best and currently only option to improve its dismal prognosis (
Pancreatic juice can be considered a good surrogate of the status of the pancreatic duct epithelium, since it contains exfoliated cells from all areas of the pancreas (
Aberrant promoter methylation of tumor suppressor genes is a frequent and early event in multiple tumors, including carcinomas of the pancreas and the periampullary area (
The aim of the present study was to assess the prevalence of the promoter methylation detection of the above panel of genes in pancreatic juice using methylation specific-melting curve analysis (MS-MCA), a sensitive and robust technique for the analysis of promoter methylation status (
Between January 2004 and December 2010, a total of 135 patients undergoing surgical resection at the Hospital Universitari de Bellvitge (L'Hospitalet de LLobregat, Barcelona) due to pancreatic disease were prospectively included in a study aimed to identify novel biomarkers in pancreatic diseases. The diagnosis was as follows: 85 PCs (9.4% of which were well differentiated, 75.3% moderately differentiated and 15.3% poorly differentiated), 26 ampullary carcinomas (ACs) (21 of the pancreaticobiliary subtype and 5 of the intestinal subtype), 10 IPMNs (2 with invasive carcinoma and 1 with carcinoma
The intraoperative pure pancreatic juice (PPJ) was snap frozen immediately after collection. DNA extraction was directly performed from the PPJ with no further processing. A modified standard phenol-chloroform method was used to optimize DNA extraction (
MS-MCA was used (
The analytical sensitivity and robustness of the method were assessed using serial dilutions of methylated DNA in increasing amounts of unmethylated DNA (
The Fisher's exact test for categorical data was used to evaluate the association between each methylation marker and diagnosis. Differences in the prevalence of markers among groups were assessed by the exact McNemar test. Diagnostic classifiers from methylation panels were estimated using the random forests test. Software R version 3.2.0 (
Promoter analysis was informative in the majority of cases [
The prevalence of methylation in CP was low for all analyzed markers (0–14%), being only negative for the
As an individual marker,
The mutation analysis of
In order to assess the impact of sampling in the performance of the test in pancreatic juice, the
The present study has identified
Regarding the other markers analyzed in the present study,
When assessing pancreatic juice, the present panel did not add information to APC as a single marker. The high prevalence of
The pancreatic juice provides information from cells shed from all areas of the pancreatic epithelium, thus yielding a comprehensive sampling of the target organ (
As discussed above, sampling may be a relevant issue when assessing genetic or epigenetic aberrations in pancreatic juice. However, the present authors do not consider that the use of anterograde collection during surgery is worse than retrograde collection of pancreatic juice during endoscopic retrograde cholangiopancreatography (ERCP) or collection of duodenal juice after secretin stimulation. The high yield of
Age and chronic inflammation may affect DNA methylation (
The robustness of the present results may be partially attributable to the use of MS-MCA, a reliable technique that assesses the hypermethylation status of all CpG included in the amplicon analyzed. This technique was selected due to its simplicity, reproducibility and analytical sensitivity, which enables the detection of ≤5% of methylated alleles (
In conclusion, the present study has observed that
The present study was supported by grants from the Carlos III Health Institute, which is seconded to the Ministry of Economy and Competitiveness (Madrid, Spain) and the European Regional Development Fund (EDRF) (Brussels, Belgium) (grant nos. FIS PI060415 and PIE PIE13/00022); Research Foundation in Gastroenterology (Barcelona, Spain) (grant no. F05-01); the Ministry of Education and Science (Madrid, Spain) (grant nos. SAF2011/23638, SAF2015-68016-R and SAF2012-33636); the Thematic Network of Cooperative Research in Cancer (Madrid, Spain) (grant no. RD12/0036/0031); the Spanish Association Against Cancer Scientific Foundation (Madrid, Spain); and the Government of Catalonia (Barcelona, Spain) (grant nos. 2009 SGR 1356 and 2014 SGR 338). In addition, the current study was co-funded by FEDER funds/EDRF - a way to build Europe.
fine-needle aspiration
quantitative polymerase chain reaction
melting curve analysis
pancreatic cancer
ampullary carcinoma
intraductal papillary mucinous neoplasm
chronic pancreatitis
pure pancreatic juice
Analytical sensitivity of the detection of methylated alleles using methylation specific-melting curve analysis of the methylation status of the
Proportion of methylated samples according to sample type. *P<0.05 PC vs. AC; †P<0.05 AC vs. IPMN; ‡P<0.05 CP vs. PC, AC and IPMN. PC, pancreatic cancer; AC, ampullary carcinoma; IPMN, intraductal papillary mucinous neoplasm; NP, neoplasm of pancreatic area (all types of tumors together); CP, chronic pancreatitis;
Proportion of methylated samples when considering all markers as a panel (≥2 hypermethylated markers) and proportion of samples with methylated
Main characteristics of the study population.
Characteristics | PC | AC | IPMN | CP |
---|---|---|---|---|
Patients (n) | 85 | 26 | 10 | 14 |
Age (years) | 62±12 | 71±8 | 66±14 | 47±12 |
Gender (M/F) | 44/41 | 17/9 | 8/2 | 12/2 |
Not applicable | 7 | 14 | ||
Not available | 1 | |||
TNM stage | ||||
T1N0 | 2 | 3 | ||
T2N0 | 9 | |||
T2N1 | 6 | |||
T3N0 | 14 | 3 | 2 | |
T3N1M0 | 60 | 4 | ||
T3N1M1 | 3 | |||
T4N1M0 | 4 | |||
T4N1M1 | 1 | |||
1 | 1 |
PC, pancreatic cancer; AC, ampullary carcinoma; IPMN, intraductal papillary mucinous neoplasm; CP, chronic pancreatitis; M, male; F, female; TNM, tumor-node-metastasis.
DNA hypermethylation and
A, Primer sequences and PCR conditions for DNA hypermethylation analysis | |||||
---|---|---|---|---|---|
Gen | PCR | Annealing temperature (°C) | CpG (n) | Primers sequence (5′→3′) | |
External | 52 | 28 | F: ACTATCCTACTTATAAACTC | ||
R: AGAATAATAAAGATAAGAGAT | |||||
Nested | 54 | F: CTACTTATAAACTCAACCAA | |||
R: GTTTTAGGGATTTAGAGTTT | |||||
External | 56 | 18 | F: GGGTGGATTTGGAAAGTGT | ||
R: TTACTCTACTCATCCCACAA | |||||
Nested | 62 | F: GGGTGGATTTGGAAAGTGT | |||
R: TCCAAATATCCCCAACAAAA | |||||
External | 54 | 16 | F: TGGAGGGGAGATAGATTTAGTT | ||
R: AACCAAAAACAAACACAAAAAA | |||||
Nested | 58 | F: TTTTGAGTGGTTTTTTGTTGTT | |||
R: ATCCACCTTCTAAAAAACAACAA | |||||
64 | 16 | F: GGTTAGGGTTAGGTAGGTTG | |||
R: CTACACCAATACAACCAC | |||||
65 | 23 | F: TGATTTGTGAGGTTGAGTTTTAA | |||
R: ACCCCTCTTCCCTACCTAAAA | |||||
B, |
|||||
Codon |
Aminoacid | WT | Mutation | Control cell line | Probe sequence (5′→3′) |
12 | – | GGT | – | NP18 | TTGGAGCTGGTGGCGTA |
12 | G12C | GGT | TGT | MIA PaCa-2 | TTGGAGCTTGTGGCGTA |
12 | G12V | GGT | GTT | SW480 | TTGGAGCTGTTGGCGTA |
12 | G12D | GGT | GAT | NP9 | TTGGAGCTGATGGCGTA |
12 | G12A | GGT | GCT | SW1116 | TTGGAGCTGCTGGCGTA |
12 | G12S | GGT | AGT | A549 | TAGTTGGAGCTAGTGGCGTA |
12 | G12R | GGT | CGT | CAL-62 | TTGGAGCTCGTGGCGTA |
13 | – | GGC | – | NP18 | CTTGCCTACGCCACCAG |
13 | G13D | GGC | GAC | DLD-1 | CTTGCCTACGTCACCAG |
Forward primer codons 12 and 13, 5′-GCCTGCTGAAAATGACTGAATATAAACT-3′; reverse primer codon 12, 5′-GCTGTATCGTCAAGGCACTCTT-3′; reverse primer codon 13, 5′-GAATTAGCTGTATCGTCAAGGCACT-3′. PCR, polymerase chain reaction;
Prevalence of all methylation markers analyzed and KRAS codons 12 and 13 mutations depending on tumor type
Cancer | Met |
Met |
Met |
Met |
Met |
≥2 Met markers | Mut KRAS |
---|---|---|---|---|---|---|---|
PC | 71% | 65% | 57% | 49% | 37% | 72% | 50% |
(59/83) | (53/82) | (44/77) | (35/72) | (29/78) | (61/83) | (41/82) | |
AC | 76% | 43% | 27% | 32% | 26% | 56% | 42% |
(19/25) | (10/23) | (6/22) | (7/22) | (6/23) | (14/25) | (11/26) | |
IPMN | 80% | 90% | 55% | 67% | 50% | 80% | 55% |
(8/10) | (9/10) | (5/9) | (6/9) | (5/10) | (8/10) | (5/9) | |
NP | 73% | 63% | 51% | 47% | 36% | 70% | 47% |
(86/118) | (72/115) | (55/108) | (48/103) | (40/111) | (83/118) | (57/117) | |
CP | 7% | 14% | 0% | 8% | 7% | 7% | 33% |
(1/14) | (2/14) | (0/14) | (1/13) | (1/14) | (1/14) | (4/14) |
Percentages are expressed on the total number of informative amplified samples. Met, methylated; Mut, mutated; PC, pancreatic cancer; AC, ampullary carcinoma; IPMN, intraductal papillary mucinous neoplasms; NP, neoplasm of pancreatic area (all types of tumors together); CP, chronic pancreatitis;
Sensitivity and specificity of each methylation marker separately and combined (panel), and sensitivity and specificity of KRAS mutations detection separately and in combination with the panel of methylation markers.
Sensitivity % (95% CI) | ||||||||
---|---|---|---|---|---|---|---|---|
Comparison | Panel | |||||||
PC vs. CP | 71% | 65% | 57% | 49% | 37% | 72% | 52% | 78% |
(61–80) | (54–74) | (46–67) | (37–60) | (27–48) | (61–80) | (41–62) |
(68–85) | |
AC vs. CP | 76% | 43% | 27% | 32% | 26% | 54% | 44% | 69% |
(57–88) | (26–63) | (13–48) | (16–53) | (12–46) | (35–71) | (26–63) | (50-83) | |
IPMN vs. CP | 80% | 90% | 56% | 67% | 50% | 80% | 56% | 80% |
(49–94) | (59–98) | (26–81) | (35–88) | (23–76) | (49–94) | (26–81) | (49–94) | |
NP vs. CP | 73% | 63% | 51% | 47% | 36% | 69% | 50% | 76% |
(64–80) | (53–70) | (41–60) | (37–56) | (27–45) | (60–76) | (41–59) |
(68–83) |
|
Specificity | 93% | 86% | 100% | 92% | 93% | 93% | 71% | 79% |
(95% CI) | (69–99) | (60–96) | (78–100) | (67–99) | (68–98) | (68–99) | (45–88) | (52%-92) |
P<0.05 panel vs. KRAS. PC, pancreatic cancer; AC, ampullary carcinoma; IPMN, intraductal papillary mucinous neoplasm; NP, neoplasm of pancreatic area (all types of tumors together); CP, chronic pancreatitis; CI, confidence interval;