Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer

Kwon, Min-Seok; Kim, Yongkang; Lee, Seungyeoun; Namkung, Junghyun; Yun, Taegyun; Yi, Sung Gon; Han, Sangjo; Kang, Meejoo; Kim, Sun Whe; Jang, Jin-Young; Park, Taesung

doi:10.1186/1471-2164-16-S9-S4

BMC Genomics

Table 1 Performance of multi-markers.

From: Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer

miRNA							Target gene
	PDAC dataset			Independent dataset				PDAC dataset				Independent dataset
miRNA	regulation	BA	AUC	PDAC1	PDAC2	PDAC3	target gene	corr^a	p-value^b	BA	AUC	PDAC1	PDAC2	PDAC3
miR-107	up	0.859	0.851	0.800	0.729	0.670	DTNA	-0.625	1.34E-14	0.936	0.937	0.937	0.795	0.810
							IFRD1	-0.593	6.44E-13	0.932	0.988	0.949	0.782	0.550
							KIAA1324	-0.636	3.30E-15	0.932	0.975	0.920	0.795	0.762
							BTG2	-0.629	8.12E-15	0.917	0.982	0.800	0.705	0.550
							NTRK2	-0.499	4.83E-09	0.889	0.905	0.823	0.705	0.772
							VTCN1	-0.309	5.39E-04	0.880	0.748	0.829	0.705	0.720
							SGK1	-0.451	1.85E-07	0.871	0.852	0.817	0.667	0.550
							ATP8A1	-0.427	9.36E-07	0.864	0.882	1.000	0.769	0.678
							USP2	-0.464	7.14E-08	0.864	0.894	0.960	0.744	0.633
							PHF17	-0.600	2.80E-13	0.863	0.941	0.954	0.705	0.932
miR-135b	up	0.870	0.935	0.869	0.708	0.713	BACE1	-0.599	3.18E-13	0.941	0.967	1.000	0.821	0.786
							DTNA	-0.525	5.24E-10	0.936	0.937	1.000	0.795	0.810
							PELI2	-0.528	4.08E-10	0.927	0.973	1.000	0.769	0.772
							VLDLR	-0.635	4.25E-15	0.922	0.969	1.000	0.756	0.741
							RRBP1	-0.388	1.03E-05	0.913	0.995	1.000	0.821	0.550
							MKNK1	-0.603	1.88E-13	0.902	0.953	1.000	0.744	0.786
							BCAT1	-0.524	6.04E-10	0.893	0.939	1.000	0.859	0.713
							SEMA6D	-0.498	5.38E-09	0.893	0.904	1.000	0.769	0.762
							ATP8A1	-0.437	4.95E-07	0.864	0.882	1.000	0.769	0.678
							PHF17	-0.575	4.54E-12	0.863	0.941	1.000	0.705	0.932
miR-148a	down	0.927	0.956	0.897	0.788	0.688	SLC2A1	-0.486	1.41E-08	0.962	0.987	0.914	0.756	0.550
							MBOAT2	-0.404	3.96E-06	0.929	0.951	0.926	0.872	0.869
							TRAK1	-0.371	2.60E-05	0.905	0.973	0.863	0.692	0.793
							SULF1	-0.494	7.54E-09	0.878	0.864	0.800	0.923	0.755
							KLF5	-0.425	1.10E-06	0.870	0.870	0.926	0.769	0.835
							LRCH1	-0.312	4.63E-04	0.865	0.916	0.909	0.654	0.772
							ETV1	-0.325	2.57E-04	0.855	0.875	1.000	0.846	0.724
miR-21	up	0.897	0.925	0.903	0.725	0.687	DTNA	-0.559	2.28E-11	0.936	0.937	0.937	0.795	0.810
							IFRD1	-0.532	2.80E-10	0.932	0.988	0.949	0.782	0.550
							BTG2	-0.648	6.89E-16	0.917	0.982	0.800	0.705	0.550
							BCAT1	-0.551	5.04E-11	0.893	0.939	0.903	0.859	0.713
							NTRK2	-0.444	2.92E-07	0.889	0.905	0.823	0.692	0.772
							LIFR	-0.596	4.64E-13	0.888	0.964	0.903	0.769	0.918
							ACAT1	-0.511	1.81E-09	0.875	0.830	1.000	0.795	0.550
							PHF17	-0.609	1.03E-13	0.863	0.941	0.954	0.705	0.932
							SNTB1	-0.449	2.21E-07	0.855	0.802	1.000	0.769	0.585
miR-222	up	0.924	1.012	0.869	0.736	0.759	CXCL12	-0.452	1.69E-07	0.932	0.970	0.851	0.705	0.932
miR-34a	up	0.908	0.912	0.806	0.742	0.670	DTNA	-0.447	2.43E-07	0.936	0.937	0.937	0.795	0.810
							BCAT1	-0.514	1.46E-09	0.893	0.939	0.903	0.859	0.713

^a.correlation coefficient between miRNA mRNA expression. ^b.p-value from linear regression with miRNA and mRNA expression.

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ISSN: 1471-2164

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