Evaluating the prognostic efficacy of biomarkers in pancreatic cyst fluid

Table 2 Molecular marker studies in pancreatic cyst fluid

Ref.	Type of study	Molecular marker	Patients	Sensitivity	Specificity	Accuracy	Conclusions
Khalid et al[51], 2005	Prospective single-center diagnostic study	KRAS codon 12, allelic loss, CEA, DNA quality	36	91%	93%	92.0%	KRAS followed by allelic loss is highly predictive for malignancy
Sawhney et al[52], 2009	Retrospective EUS-FNA study	KRAS, CEA, DNA quantity, allelic imbalance	100	82% (CEA), 77% (Mol)	-	-	CEA and molecular markers had poor concordance; combining improved sensitivity to 100%
Khalid et al[53], 2009	Multicenter prospective PANDA study	KRAS, DNA yield, LOH amplitude	113	-	KRAS 96%	-	Allelic loss and DNA quantity predicted malignancy
Nikiforova et al[54], 2013	Large retrospective cohort	KRAS codon 12	603	67% (IPMN), 14% (MCN)	100%	77%	KRAS highly specific for mucinous cysts, low sensitivity for MCNs
Singhi et al[55], 2014	Prospective surgical validation	KRAS, GNAS (codon 201)	91	65%	100%	82.5%	Highly specific for IPMNs; limited sensitivity for MCNs
Winner et al[56], 2015	Retrospective cohort study	KRAS, LOH, DNA content	56	50%	96%	73.0%	Molecular markers increased diagnostic yield, but less accurate than CEA
Rockacy et al[65], 2013	Retrospective prognostic study	KRAS	113	-	-		KRAS associated with poor clinical outcomes
Al-Haddad et al[66], 2015	Prospective multicenter IMP study	IMP (KRAS, TP53 + cytology/clinical data)	492	-	-	-	IMP outperformed Sendai guidelines in risk stratification
Springer et al[69], 2015	Prospective classifier study	KRAS, GNAS, TP53, SMAD4, LOH, BRAF	130	90%-100%	92%-98%	95%	Molecular algorithm reduced unnecessary surgeries by 91%
Jones et al[62], 2016	Prospective reclassification study	KRAS, GNAS, TP53, CDKN2A, SMAD4	92	86% (NGS)	100% (CEA)	93%	NGS reclassified cysts with normal CEA; detected high-risk lesions
Singhi et al[70], 2016	Clinicopathologic accuracy study	KRAS, GNAS, TP53, VHL, PTEN	225	100%	100%	100%	Outperformed AGA guidelines in detecting advanced neoplasia
Kadayifci et al[63], 2017	Retrospective validation study	CEA, KRAS, GNAS	197	86.2% (triple)	-	-	GNAS improved accuracy when added to CEA and KRAS
Rosenbaum et al[71], 2017	Retrospective cytology correlation	KRAS, GNAS, TP53, SMAD4	113	75% (cytology), 46% (late mutations)	-	-	NGS added value in identifying malignant cysts
Singhi et al[76], 2018	Large prospective validation	KRAS, GNAS, TP53, PTEN, PIK3CA	626	89%	100%	94.5%	High accuracy in cyst classification and risk stratification
Volckmar et al[59], 2019	Prospective biomarker study	KRAS, GNAS via NGS in cell fraction	22	100% (IPMN)	100% vs pseudocysts	100%	Mutations distinguished IPMNs from pseudocysts
Farrell et al[72], 2019	Cohort analysis with imaging features	KRAS, LOH, DNA amount	478	-	-	-	≥ 2 DNA abnormalities increased malignancy risk in cysts with worrisome features
Springer et al[75], 2019	Multimodal AI tool (CompCyst)	CompCyst (clinical + KRAS, GNAS, TP53)	862	-	-	-	Significantly improved diagnostic accuracy and reduced overtreatment
Laquière et al[73], 2019	Pilot NGS concordance study	KRAS, GNAS, TP53	17	78%	62%-100%	-	PCF and tissue mutations were concordant in 88% of cases
Ren et al[57], 2021	Prospective molecular reclassification study	KRAS, GNAS, BRAF	108	88.5%	100%	94.3%	KRAS-negative mucinous cysts had alternative BRAF pathway mutations
McCarty et al[44], 2021	Meta-analysis	KRAS, GNAS	785	94%	91%	92.5%	KRA+ GNAS significantly outperformed CEA in mucinous cyst diagnosis
Herranz Pérez et al[58], 2021	Routine practice molecular study	KRAS, GNAS	-	-	-	-	Feasibility and utility confirmed in real-world setting
Pflüger et al[61], 2023	Meta-analysis (42 studies)	TP53, SMAD4, CDKN2A, VHL	666	9%-42%	95%-99%	69.5%	High specificity for HGD; VHL for SCA discrimination
Hata et al[74], 2023	Prospective epigenetic biomarker study	TBX15, SOX17 methylation	70	69.6%	90%	79.8%	Methylation identified HGD in IPMNs
Nikiforova et al[77], 2023	PancreaSeq GC validation (DNA/RNA NGS)	74-gene panel + CEACAM5 mRNA	185	95% (precursor), 82% (HGD)	100%	97.5%	PancreaSeq GC outperformed imaging/cytology in neoplasia detection
Paniccia et al[78], 2023	Multicenter real-time NGS registry	PancreaSeq 22-gene panel	1933	93%	95%	94%	NGS with cytology guided clinical decisions
Hu et al[68], 2024	Review on progression markers	KRAS, GNAS (prognostic)	-	-	-	-	GNAS may be linked to improved recurrence-free survival
Belfrage et al[64], 2024	Prospective diagnostic accuracy study	50-gene NGS, KRAS, GNAS, TP53 + CEA	97	78% (combo)	87%	82.5%	NGS + CEA improved classification and influenced surgical decisions

CEA: Carcinoembryonic antigen; EUS-FNA: Endoscopic ultrasound-guided fine-needle aspiration; AI: Artificial Intelligence; Mol: Molecular; PANDA: Pancreatic cyst DNA analysis; LOH: Loss of heterozygosity; MCN: Mucinous cystic neoplasms; IPMN: Intraductal papillary mucinous neoplasms; IMP: Integrated molecular pathology; NGS: Next-generation sequencing; HGD: High-grade dysplasia; AGA: American Gastroenterological Association; GC: Genomic classifier.