Reference | Cases | Controlsa | Relevant Genes | Methodb | Results |
---|---|---|---|---|---|
Jiao Li et al., 2007 [48] | 83 PDAC: | 0 | ppENK | MSP | p16 (9 patients): sensitivity 70%; specificity 100% |
 | 16 I-II |  |  |  |  |
 | 37 III |  | p16 |  |  |
 | 30 IV |  |  |  |  |
Melnikov et al., 2009 [68] | 34 PDAC: 19 I-II 2 III 13 IV | 30 HC | CCND2 | MethDet56 | Based on the unmethylated status of the composited biomarker: sensitivity 76%; specificity 59% |
 |  |  | SOCS1 |  |  |
 |  |  | THBS |  |  |
 |  |  | PLAU |  |  |
 |  |  | VHL |  |  |
Ligget et al., 2010 [69] | 30 PDAC | 30HC 30CP | BRCA12 CCND21,2 CDKN1C1,2 CDKN2B1 DAPK11 ESR11 MGMT1 MLH11,2 MUC21 MYOD11 PGK11 PGR proximal1,2 PGR distal2 RARB1 RB11 SYK1,2 | MethDet56 | 1Methylation of 14 gene promoters distinguishes between CP and PDAC: sensitivity 91.2% (95% CI 76.5-97.1); specificity 90.8% (95% CI 76.1-96.8) 2Methylation of 8 gene promoters distinguishes between HC and CP: sensitivity 81.7% (95% CI 67.3-90.6); specificity 78% (95% CI 63.8-87.7) |
Melson et al., 2014 [70] | 30 PDAC: 18 I-II 5 III 7 IV | 30 HC | VHL | MethDet56 | Combined 5 markers to differentiate PDAC from HC: sensitivity 80%; specificity 66% GPC3: sensitivity 63.3%; specificity 83.3% |
MYF3 | |||||
TMS | |||||
GPC3 | |||||
SRBC | |||||
Park et al., 2012 [71] | 16 PDAC: 1 I 8 III 7IV | 29 HC | UCHL1 | MSP + bisulfite sequencing | Higher methylation detection in PDAC compared to HC (p<0.05) |
NPTX2 | |||||
SARP2 | |||||
13 CP | ppENK | Methylated p16 significantly higher in PDAC than in CP (p = 0.016) | |||
p16 | |||||
RASSF1A | |||||
Park et al., 2012 [72] | 104 PDAC: | 60 CP | NPTX2 | qMSP | NPTX2: sensitivity 80%; specificity 76% |
24 I-II | 5 benign biliary tract stone disease | ||||
43 III | |||||
37 IV | |||||
Kawasaki et al., 2013 [73] | 47 PDAC | 197: colon, lung, gastric, breast cancers and hepatocarcinoma | APC | MSP | Methylation frequencies: |
DCC | |||||
p16 | RASSF1A 34% APC 23.4% | ||||
p14 | p16 17% p14 14.9% | ||||
RASSF1A | DCC 6.4% | ||||
Yi et al., 2013 [74] | 42 PDAC: 10 I 32 II-IV | 26 HC | BNC1 | MOB | BNC1: sensitivity 79% (95% CI 66-91); specificity 89% (95% CI 76-100) |
ADAMTS1: sensitivity 48% (95% CI 33-63); specificity 92% (95% CI 82-100) | |||||
ADAMTS1 | BNC1+ADAMTS1: sensitivity 81% (95% CI 69-93); specificity 85% (95% CI 71-99) | ||||
90% sensitivity in stage I for both genes | |||||
Henriksen et al., 2016 [75] | 95 PDAC: 40 I-II 13 III 42 IV | 97 CP | APC | MSP + qMSP | Diagnostic prediction model with 8 genes methylation panel that differentiate malign from benign conditions: AUC=0.86 (95% CI 0.81-0.91), sensitivity 76%; specificity 83% Performance of prediction model in early-stages (I-II): AUC=0.86 (95% CI 0.79–0.92), 73% sensitivity; 83% specificity |
BMP3 | |||||
59 acute pancreatitis | BNC1 | ||||
MESTv2 | |||||
RASSF1A | |||||
27 benign conditions | SFRP1 | ||||
SFRP2 | |||||
TFPI2 | |||||
Henriksen et al., 2017 [76] | 95 PDAC: 40 I-II 13 III 42 IV | 0 | ALX4 1,2 | MSP | Two methylation-based prognostic prediction models: |
BNC1 1,2 | |||||
CDKN2B 1,2 | |||||
HIC1 1 | 1Methylation of 8 genes that differentiate stage IV from stage I-III disease: AUC=0.87, sensitivity 74%; specificity 87% | ||||
MLH1 1,2 | |||||
NEUROG1 1,2 | |||||
SEPT9v2 1,2 | 2Methylation of 8 genes that differentiate stage I-II from stage III-IV disease: AUC=0.82, sensitivity 73%; specificity 80% | ||||
SST 1 | |||||
TFPI2 2 | |||||
WNT5A 2 | |||||
Henriksen et al., 2017 [77] | 95 PDAC: 40 I-II 13 III 42 IV | 0 | BNC1 | MSP | Gene hypermethylation based survival prediction model (Hazard ratios (95% CI)): BNC1 2.00 (1.26-3.18); GSTP1 9.55 (2.70-33.82); SFRP1 1.94 (1.24-3.02); SFRP2 0.45 (0.27-0.73) and TFPI2 2.52 (1.42-4.47) |
GSTP1 | |||||
SFRP1 | |||||
SFRP2 | |||||
TFPI2 | |||||
Eissa et al., 2019 [78] | 39 PDAC: 37 I-II 2 III-IV | 95 HC 8 CP | BNC1 ADAMTS1 | qMSP | BCN1: AUC=0.79 (95% CI 0.70-0.85), sensitivity 64.1%; specificity 93.7% ADAMTS1: AUC=0.91 (95% CI 0.85-0.95) sensitivity 87.2%; specificity 95.8% BNC1 + ADAMTS1: AUC=0.95 (95% CI 0.90-0.98) sensitivity 97.4%; specificity 91.6% |
Li et al., 2019 [79] | 57 PDAC | 53 HC | BNC1 SEPT9 | qMSP | BCN1: sensitivity 50.9% (95% CI 37.3-64.4); specificity 88.7% (95% CI 77.0-95.7) SEPT9: sensitivity 36.8% (95% CI 24.5-50.7); specificity 96.2% (95% CI 87.0-99.5) BNC1 + SEPT9: sensitivity 64.9% (95% CI 55.0-78.8); specificity 86.8% (95% CI 74.7-94.5) Combined genes + CA19-9: sensitivity 86% (95% CI 74.2-93.7); specificity 81.1% (95% CI 68.0-90.6) |
14 PanIN | |||||
44 benign conditions | |||||
Singh et al., 2020 [80] | 61 PDAC: 20 I-II 38 III-IV 2 unspecified | 22 HC | UCHL1 PENK NPTX2 SPARC | qMSP | Methylation index (MI) of 4 genes higher in PDAC than in HC (p < 0.05) Lower survival in patients with high MI for SPARC and NPTX2 genes (p < 0.05) |
21 CP | |||||
Shinjo et al., 2020 [81] | 47 PDAC: 2 II 41 III-IV 4 unknown | 14 HC | ADAMTS2 HOXA1 PCDH10 SEMA5A SPSB4 | MBD-ddPCR | Methylation levels in the 5 genes not significantly different between PDAC and HC 49% of PDAC patients with at least one methylated gene, 49% sensitivity; 86% specificity DNA methylation in ≥ 1 gene and/or KRAS mutation: sensitivity 68%; specificity 86% |
Li et al., 2020 [82] | 4 PDAC: 2 II 2 III | 2 HC | TRIM73 | MeDIP-seq | Combined 8 gene panel: sensitivity 97.1%; specificity 98% |
FAM150A | |||||
EPB41L3 | |||||
SIX3 | |||||
MIR663 | |||||
MAPT | |||||
LOC100128977 | |||||
LOC100130148 | |||||
Manoochehri et al., 2020 [83] | 30 PDAC: 15 nonmetastatic 15 metastatic | 18 HC | SST | ddPCR | SST: sensitivity 93%; specificity 89% |
Cao et al., 2020 [84] | 67 PDAC: 8 I 26 II 17 III 16 IV | 97 HC | 5mC 5hmC | MeDIP-seq 5hmC sequencing (hMe-Seal) | A 24-feature 5mC model that can discriminate PDAC from HC, sensitivity 82.4%; specificity 100% A 27-feature 5hmC model that can discriminate PDAC from HC, sensitivity 85.7%; specificity 100% The 51-feature model combining 5mC and 5hmC markers: sensitivity 93.8%; specificity 95.5% |
Ying et al., 2021 [85] | 22 PDAC: | 10 HC | ADAMTS1 BNC1 LRFN5 PXDN | MOB-qMSP | Pancreatic cancer detection with 4-gene panel: AUC=0.94, sensitivity 100%; specificity 90% |
3 I | |||||
15 II | |||||
1 III-IV | |||||
3 not available | |||||
Henriksen et al., 2021 [86] | 346 PDAC: 11 I 165 II 33 III 137 IV | 25 CP | APC | MSP | Validation study of the diagnostic prediction model proposed in Henriksen et al., 2016: AUC=0.77 (95% CI 0.69-0.84) Diagnostic prediction model + CA19-9 in: Resectable disease (I-II): AUC=0.89 (95% CI 0.83-0.95) Unresectable disease (IV): AUC=0.95 (95% CI 0.92-0.98) Entire cohort: AUC=0.85 (95% CI 0.79-0.91) |
BMP3 | |||||
BNC1 | |||||
MESTv2 | |||||
RASSF1A | |||||
SFRP1 | |||||
SFRP2 | |||||
TFPI2 | |||||
Majumder et al., 2021 [87] | 170 PDAC: 5 I 45 II 60 III 60 IV | 170 HC | GRIN2D | TELQAS assay | Methylated DNA marker (MDM) panel: AUC=0.90 (95% CI 0.86-0.94) MDM panel + CA 19-9: AUC=0.97 (95% CI 0.94-0.99), sensitivity 92% (95% CI 83-98); specificity 92% (95% CI 81-100) MDM panel for early-stage detection: AUC=0.84 (95% CI 0.76-0.92) MDM + CA19-9 for early-stage detection: AUC=0.90 (95% CI 0.84-0.97) |
CD1D | |||||
ZNF781 | |||||
FER1L4 | |||||
RYR2 | |||||
CLEC11A | |||||
AK055957 | |||||
LRRC4 | |||||
GH05J042948 | |||||
HOXA1 | |||||
PRKCB | |||||
SHISA9 | |||||
NTRK3 | |||||
Miller et al., 2021 [88] | 25 PDAC: 1 I 7 II 4 III 13 IV | 20 HC | ZNF154 | MOB-DREAMing | ZNF154 for early stage (I-II): AUC=0.87, sensitivity 100% and specificity 80% ZNF154 for late stage (III-IV): AUC=0.85, sensitivity 94.1% and specificity 80% |
Vrba et al., 2022 [89] | 19 PDAC 19 IV | 44 benign conditions | MIR129-2 LINC01158 CCDC181 PRKCB TBR1 ZNF781 MARCH11 VWC2 SLC9A3 HOXA7 | qMSP | Biomarker set of 10 genes capable of distinguishing malignant from benign cases: AUC=0.999 (95% CI 0.995-1.0) sensitivity 100% and specificity 95% Biomarker set useful for monitoring: methylation decrease after treatment (p=3.9x10-3) |
GarcÃa-Ortiz et al., 2023 [90] | 44 PDAC 44 IV | 2 HC | BMP3 NPTX2 SFRP1 SPARC TFPI2 | ddPCR | NPTX2 methylation distinguished between low- and high-risk poor prognosis patients (p-=6.7x10-3) NPTX2 methylation dynamics during patients monitoring predict evolution disease and survival: AUC=0.80 (95% CI 0.66-0.94), sensitivity 85%; specificity 65% |