MassARRAY-based KRAS and GNAS hotspot mutation analysis of cystic fluid enables accurate classification of pancreatic cystic lesions

doi:10.3748/wjg.v32.i13.115710

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Apr 7, 2026 (publication date) through Mar 27, 2026

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastroenterol. Apr 7, 2026; 32(13): 115710
Published online Apr 7, 2026. doi: 10.3748/wjg.v32.i13.115710

Table 1 Patient characteristics, n (%)

	IPMNs (n = 23)	MCNs (n = 36)	SCAs (n = 32)	Non-neoplastic cysts (n = 10)	P value
Gender					< 0.001
Male	14 (60.9)	0 (0)	6 (18.8)	2 (20)
Female	9 (39.1)	36 (100)	26 (81.3)	8 (80)
Age (years)	64.22 (5.93)	41.81 (13.04)	45.25 (14.75)	36.2 (8.77)	< 0.001
Location					0.007
Head	11 (47.8)	3 (8.3)	7 (21.9)	2 (20)
Body or tail	10 (43.5)	33 (91.7)	23 (71.9)	8 (80)
Head and body or tail	2 (8.7)	0 (0)	2 (6.3)	0 (0)
Cyst diameter (mm)	43.09 (17.81)	56.79 (33.5)	48.88 (18.49)	68.1 (27.63)	0.046
Cyst diameter ≥ 30 mm					0.213
Yes	17 (73.9)	33 (91.7)	31 (96.9)	9 (90)
No	5 (21.7)	2 (5.6)	1 (3.1)	1 (10)
Main pancreatic duct dilation (≥ 4 mm)					< 0.001
Yes	16 (69.6)	2 (5.6)	6 (18.8)	1 (10)
No	7 (30.4)	34 (94.4)	26 (81.3)	8 (80)
Bile duct dilation (≥ 7 mm)					0.041
Yes	4 (17.4)	1 (2.8)	0 (0)	0 (0)
No	18 (78.3)	34 (94.4)	32 (100)	9 (90)
Serum CEA (ng/mL)	3.48 (4.31)	1.49 (2)	1.49 (0.98)	1.29 (1.08)	0.012
Elevated serum CEA (≥ 5 ng/mL)					0.001
Yes	5 (21.7)	1 (2.8)	1 (3.1)	0 (0)
No	18 (78.3)	34 (94.4)	31 (96.9)	8 (80)
Serum CA19-9 (U/mL)	34.8 (53.56)	25.32 (35.41)	20.73 (29.65)	16.29 (13.33)	0.486
Elevated serum CA19-9 (≥ 34 U/mL)					0.097
Yes	3 (13)	7 (19.4)	3 (9.4)	1 (10)
No	20 (87)	29 (80.6)	29 (90.6)	8 (80)
Total bilirubin (μmol/L)	15.34 (7.97)	14.34 (5.85)	12.91 (5.76)	12.73 (3.57)	0.463
Elevated total bilirubin (≥ 22.2 μmol/L)					0.184
Yes	4 (17.4)	5 (13.9)	1 (3.1)	0 (0)
No	19 (82.6)	31 (86.1)	31 (96.9)	10 (100)
Direct bilirubin (μmol/L)	6.38 (6.59)	4.44 (1.6)	4.22 (2.52)	4.21 (1.32)	0.124
Elevated direct bilirubin (≥ 6.8 μmol/L)					0.563
Yes	4 (17.4)	4 (11.1)	4 (12.5)	0 (0)
No	19 (82.6)	32 (88.9)	28 (87.5)	10 (100)

IPMNs: Intraductal papillary mucinous neoplasms; MCNs: Mucinous cystic neoplasms; SCAs: Serous cystadenomas; CEA: Carcinoembryonic antigen; CA19-9: Cancer antigen 19-9.

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Table 2 Summary of hotspot mutation analysis, n (%)

Hotspot mutation		IPMNs (n = 23)	MCNs (n = 36)	SCAs (n = 32)	Non-neoplastic cysts (n = 10)
KRAS	Wild type	14 (60.9)	25 (69.4)	32 (100)	10 (100)
	Hotspot mutation	9 (39.1)	11 (30.6)	0 (0)	0 (0)
	G12D	3 (13)	3 (8.3)	0 (0)	0 (0)
	G12V	4 (17.4)	4 (11.1)	0 (0)	0 (0)
	G12R	0 (0)	1 (2.8)	0 (0)	0 (0)
	Q61H¹	1 (4.3)	2 (5.6)	0 (0)	0 (0)
	A146V²	4 (17.4)	3 (8.3)	0 (0)	0 (0)
GNAS	Wild type	11 (47.8)	36 (100)	32 (100)	10 (100)
	Hotspot mutation	12 (52.2)	0 (0)	0 (0)	0 (0)
	R201C	4 (17.4)	0 (0)	0 (0)	0 (0)
	R201H	8 (34.8)	0 (0)	0 (0)	0 (0)

¹One mucinous cystic neoplasm cystic fluid sample did not call any results at KRAS codon 61.

²Two serous cystadenomas cystic fluid samples did not call any results at KRAS codon 146.

IPMNs: Intraductal papillary mucinous neoplasms; MCNs: Mucinous cystic neoplasms; SCAs: Serous cystadenomas.

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Table 3 Performance of different diagnostic modalities

	Sensitivity (95%CI)	Specificity (95%CI)
Identification of mucinous neoplasms among all PCLs
Integrated prediction model	62.7% (50.4%-75.1%)	95.2% (88.8%-100%)
KRAS/GNAS mutation panel	40.7% (28.1%-53.2%)	100% (100%-100%)
Clinical characteristics and serum markers	37.3% (24.9%-49.6%)	95.2% (88.8%-100%)
Identification of IPMNs among all PCLs
Integrated prediction model	82.6% (67.1%-98.1%)	100% (100%-100%)
KRAS/GNAS mutation panel	52.2% (31.8%-72.6%)	100% (100%-100%)
Clinical characteristics and serum markers	78.3% (61.4%-95.1%)	80.8% (72.0%-89.5%)
Identification of mucinous neoplasms among PCLs in pancreatic head
Integrated prediction model	87.5% (71.3%-100%)	100% (100%-100%)
KRAS/GNAS mutation panel	56.2% (31.9%-80.6%)	100% (100%-100%)
Clinical characteristics and serum markers	62.5% (38.8%-86.2%)	100% (100%-100%)
Identification of IPMNs among PCLs
Integrated prediction model	84.6% (65%-100%)	100% (100%-100%)
KRAS/GNAS mutation panel	46.2% (19.1%-73.3%)	100% (100%-100%)
Clinical characteristics and serum markers	69.2% (44.1%-94.3%)	92.9% (79.4%-100%)

IPMNs: Intraductal papillary mucinous neoplasms; PCLs: Pancreatic cystic lesions.

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Citation: Diao WF, Cui M, Chen TQ, Xiao JH, Yang S, Zheng QY, Xu RY, Han XL, Hu Y. MassARRAY-based KRAS and GNAS hotspot mutation analysis of cystic fluid enables accurate classification of pancreatic cystic lesions. World J Gastroenterol 2026; 32(13): 115710
URL: https://www.wjgnet.com/1007-9327/full/v32/i13/115710.htm
DOI: https://dx.doi.org/10.3748/wjg.v32.i13.115710