. 2022 Dec 3;11(1):114–130. doi: 10.1002/ueg2.12328

TABLE 1.

Salivary and tongue coating biomarkers for gastric cancer and atrophic gastritis detection with available expression and AUC data

Gastric cancer detection
Type of biomarker	Biomarker^Ref.	Expression in GC	AUC (95% CI)	p‐value	Sensitivity (%)	Specificity (%)	With validation
Saliva
Lectins	AAL ²⁰	↓	0.98 (0.97–1.00)	<0.001	92.0	95.0	No
	ECA ²⁰	↑	0.86 (0.80–0.93)	<0.001	72.0	88.0	No
	VVA ²⁰	↑	0.96 (0.93–0.99)	<0.001	85.0	94.0	No
RNA	mRNA PPL ²¹	↓	0.72	NA	63.0	64.0	Validation set
RNA	miR‐140‐5p ²⁵	↓	0.70 (0.64–0.78)	NA	NA	NA	Validation set
Proteins	CSTB ²⁷	↓	0.73 (0.60–0.83)	0.002	83.9	71.0	No
Proteins	DMBT1 ²⁷	↑	0.74 (0.61–0.84)	<0.001	80.7	64.5	No
Models^Ref.
10 amino acids SERS spectra bands ¹⁶			NA	NA	94.8	90.2	No
Bacterial genera ¹⁸			0.91 (0.78–0.99)	NA	NA	NA	CV
2 lectins (SBA and VVA) ²⁰			0.89 (0.80–0.99)	<0.001	96.0	80.0	Validation set
3 mRNAs and 2 miRNAs ^a ²⁵			0.81 (0.72–0.89)	NA	75.0	83.0	Validation set
3 mRNAs, 2 miRNAs ^a and demographic factors ²⁵			0.87 (0.80–0.93)	NA	82.0	77.0	Validation set
3 proteins (CSTB, TPI1, DMBT1) ²⁶			0.93	NA	85.0	80.0	Pre‐validation
Oral swab
Oral microbiota (13 OTUs) ²³			0.82 (0.73–0.92)	NA	NA	NA	Pre‐validation
Tongue coating
6 bacterial genera ^b ²⁸			0.88 (0.80–0.95)	NA	NA	NA	Pre‐validation

Atrophic gastritis detection
Type of biomarker	Biomarker^Ref.	Expression in GC	AUC (95% CI)	p‐value	Sensitivity (%)	Specificity (%)	With validation
Saliva
Lectins	DSA ²⁰	↓	0.97 (0.95–1.00)	< 0.001	87.0	96.0	No
	LEL ²⁰	↑	0.96 (0.93–1.00)	< 0.001	93.0	92.0	No
	VVA ²⁰	↑	0.81 (0.71–0.91)	<0.001	70.0	91.0	Validation set
Models^Ref.
Bacterial genera ¹⁸			0.76	NA	NA	NA	CV
2 lectins (DSA and VVA) ²⁰			0.83 (0.71–0.94)	<0.001	70.0	91.0	Validation set

Note: Only molecules with reported relative abundance and reaching AUC >0.70 were included (suggested by ³⁸ as moderate accuracy). In bold are AUC values > 0.90. Pre‐validation means the biomarkers have been validated using the same population, whereas CV is a resampling validation technique that tests and trains a model using different portions of the data.

Abbreviations: AUC, area under the receiver operating characteristic (ROC) curve; CI, confidence interval; CV, cross‐validation; GC, gastric cancer; OTU, operational taxonomic units.

^{^a}

SPINK7, PPL, SEMA4B, miR‐140‐5p, and miR‐301a.

^{^b}

Fusobacterium, Peptococcus, Peptostreptococcus, Porphyromonas, Megamonas, and Rothia.