A comprehensive insight into the clinicopathologic significance of miR-144-3p in hepatocellular carcinoma

Figures & data

Figure 1 MiR-144-3p expression in HCC tissues in TCGA data.

Notes: (A) A comparison of miR-144-3p levels in 354 HCC tissues and 50 nontumor tissues in the TCGA data. The expression of miR-144-3p in TCGA data was normalized using a logarithm. (B) A comparison of miR-144-3p levels in 48 pairs of HCC tissues and adjacent nontumor tissues.
Abbreviations: HCC, hepatocellular carcinoma; TCGA, The Cancer Genome Atlas.

Figure 2 Diagnostic value of miR-144-3p in HCC.

Notes: (A) The ROC curve of miR-144-3p expression based on TCGA data (AUC =0.852, 95% CI: 0.810 to 0.894, P<0.001). (B): The ROC curve of miR-144-3p expression by qRT-PCR validation (AUC =0.867 95% CI: 0.817 to 0.916, P<0.001).
Abbreviations: AUC, area under the curve; HCC, hepatocellular carcinoma; qRT-PCR, quantitative reverse transcription-polymerase chain reaction; ROC, receiver operating characteristic; TCGA, The Cancer Genome Atlas.

Table 1 Expression of miR-144-3p and clinicopathologic parameters in HCC in TCGA

Clinicopathologic features	n	miR-141-3p expression
		Mean ± SD	t	P-value
Tissue (unmatched)
Adjacent noncancerous liver	50	10.7721±0.9156	11.998	<0.001
HCC	354	8.9139±1.5986
Tissue (matched)
Adjacent noncancerous liver	48	10.7654±0.9143	9.121	<0.001
HCC	48	8.7981±1.5061
Age, years
<60	163	8.8618±1.5367	−0.573	0.567
≥60	190	8.9598±1.6566
Gender
Male	241	8.9007±1.4400	−0.205	0.838
Female	113	8.9420±1.8999
AJCC pathologic T
T1	174	9.0404±1.5731	1.511	0.132
T2–T4	177	8.7826±1.6212
AJCC pathologic N
N0	241	8.9291±1.6087	F =0.157*	0.854
N1	3	8.4485±2.0641
NX	109	8.8825±1.5821
AJCC pathologic M
M0	256	8.9253±1.6432	F =0.139*	0.870
M1	4	8.5063±2.7689
MX	94	8.9001±1.4288
Cirrhosis
−	330	8.9345±1.6089	−0.336	0.737
+	6	9.1577±1.8607
Pathologic stage
I–II	245	9.0072±1.5695	2.222	0.027
III–IV	83	8.5577±1.6588
Vasoinvasion
−	196	8.9452±1.6424	0.250	0.803
+	105	8.8959±1.5828

Notes:

* One-way ANOVA analysis was performed. t: the effect size of t-test.

Abbreviations: AJCC, American Joint Committee on Cancer; ANOVA, analysis of variance; HCC, hepatocellular carcinoma; TCGA, The Cancer Genome Atlas.

Figure 3 MiR-144-3p expression detected by qRT-PCR validation.

Notes: (A) Ninety-five cases of HCC with matched 95 adjacent noncancerous liver tissues. (B) Metastasis. (C) TNM stage. (D) Capsule or infiltration.
Abbreviations: HCC, hepatocellular carcinoma; qRT-PCR, quantitative reverse transcription-polymerase chain reaction; TNM, tumor node metastasis.

Table 2 Expression of miR-144-3p and clinicopathologic parameters in HCC in the 95 pairs detected by qRT-PCR

Clinicopathologic features Tissue	n	miR-141 expression
		Mean ± SD	t	P-value
Tissue
Adjacent noncancerous liver	95	2.6200±0.9263	10.960	<0.001
HCC	95	1.3208±0.7594
Age, years
≥50	46	1.2772±0.8318	−0.541	0.590
<50	49	1.3618±0.6907
Gender
Male	75	1.2807 ±0.7202	−0.999	0.321
Female	20	1.4715±0.8959
Size, cm
<5	18	1.2189±0.8645	0.631	0.530
≥5	77	1.3447±0.7369
Tumor nodes
Single	52	1.4158±0.8055	1.346	0.182
Multiple	43	1.2060±0.6915
Metastasis
Without metastasis	46	1.5433±0.8504	2.840	0.006
With metastasis	49	1.1120±0.5994
TNM stage
I–II	22	1.8559±1.0146	3.070	0.001
III–IV	73	1.1596±0.5821
Portal vein tumor embolus
−	63	1.4165±0.8200	1.934	0.057
+	32	1.1325±0.5904
Vasoinvasion
−	59	1.3971±0.8052	1.315	0.192
+	36	1.1958±0.6697
Tumor capsular infiltration
With complete capsule	45	1.4833±0.7977	2.010	0.047
No capsule or infiltration	50	1.1746±0.6991
AFP
−	38	1.4739±0.8104	1.882	0.064
+	41	1.1444±0.7458
Cirrhosis
−	45	1.3487±0.7741	0.337	0.737
+	50	1.2958±0.7528

Note: t: the effect size of t-test.

Abbreviations: AFP, alpha-fetoprotein; ANOVA, analysis of variance; HCC, hepatocellular carcinoma; qRT-PCR, quantitative reverse transcription-polymerase chain reaction; TNM, tumor node metastasis.

Figure 4 Diagnostic value of miR-144-3p in AFP-positive and AFP-negative HCC.

Notes: (A) The ROC curve of miR-144-3p expression of AFP-positive HCC (AUC =0.827, 95% CI: 0.749 to 0.905, P<0.001). (B) The ROC curve of miR-144-3p expression of AFP-negative HCC (AUC =0.900, 95% CI: 0.839 to 0.960, P<0.001).
Abbreviations: AFP, alpha-fetoprotein; AUC, area under the curve; HCC, hepatocellular carcinoma; ROC, receiver operating characteristic.

Figure 5 The forest plots for the meta-analysis of miR-144-3p expression in HCC.

Notes: (A) The meta-analysis of all available data of miR-144-3p expression in HCC, compared to noncancerous tissue. (SMD =−0.854, 95% CI: −1.224 to (−0.484), P<0.001). (B) The subgroup analysis of the meta-analysis of the microarray data (SMD =−0.608, 95% CI: −0.803 to −0.412, P<0.001). Weights are from random-effects analysis.
Abbreviations: HCC, hepatocellular carcinoma; qRT-PCR, quantitative reverse transcription-polymerase chain reaction; SMD, standard mean difference; TCGA, The Cancer Genome Atlas.

Figure 6 The funnel plot of the meta-analysis of miR-144-3p expression in HCC.

Notes: (A) The funnel plot for the meta-analysis of all available data. (B) The funnel plot for the meta-analysis of the subgroup analysis of the microarray data.
Abbreviations: HCC, hepatocellular carcinoma; SE, standard error; SMD, standard mean difference.

Figure 7 The flowchart of the gene functional enrichment.

Abbreviations: HCC, hepatocellular carcinoma; KEGG, Kyoto Encyclopedia of Genes and Genomes; NLP, natural language processing; TCGA, The Cancer Genome Atlas.

Table 3 GO analysis of the targets of miR-144-3p obtained from predicted target genes, validated targets, TCGA and NLP

GO ID	Term	Count	P-value
Biologic process
0010033	Response to organic substance	26	1.07E-09
0009725	Response to hormone stimulus	19	1.56E-09
0042127	Regulation of cell proliferation	26	6.37E-09
0009719	Response to endogenous stimulus	19	7.36E-09
0048545	Response to steroid hormone stimulus	14	7.82E-09
Cellular component
0044421	Extracellular region part	24	2.48E-07
0005615	Extracellular space	18	7.64E-06
0031093	Platelet alpha granule lumen	6	1.11E-05
0005577	Fibrinogen complex	4	1.28E-05
0060205	Cytoplasmic membrane-bounded vesicle lumen	6	1.59E-05
Molecular function
0019900	Kinase binding	11	2.53E-06
0043499	Eukaryotic cell surface binding	5	1.03E-05
0043498	Cell surface binding	5	9.50E-05
0019899	Enzyme binding	15	1.18E-04

Notes: In the GO analysis of the targets of miR-144-3p obtained from the predicted target genes, the NLP analysis and the TCGA data, there were 264 available biologic processes, 32 cellular components and 26 molecular functions (P<0.05). In this table, the first five terms of the GO analysis are shown.

Abbreviations: GO, gene ontology; NLP, natural language processing; TCGA, The Cancer Genome Atlas.

Figure 8 The BINGO analysis network: BP.

Notes: Each node stands for a certain process and a larger size indicates a larger number of genes involved in the process. The colored nodes indicate statistical difference (P<0.05), and a smaller P-value of the process owns a deeper color. White-colored nodes were only used to connect the BP without statistical difference. In this figure, the terms of P<10E-06 are presented for better visualization.
Abbreviation: BP, biologic processes.

Figure 9 The BINGO analysis network: CC.

Notes: Each node stands for a certain process and a larger size indicates a larger number of genes involved in the process. The colored nodes indicate statistical difference (P<0.05), and a smaller P-value of the process owns a deeper color. White-colored nodes were only used to connect the biologic processes without statistical difference.
Abbreviation: CC, cellular components.

Figure 10 The BINGO analysis network: MF.

Notes: Each node stands for a certain process and a larger size indicates a larger number of genes involved in the process. The colored nodes indicate statistical difference (P<0.05), and a smaller P-value of the process owns a deeper color. The nodes of white color were only utilized to connect the biologic processes without statistical difference.
Abbreviation: MF, molecular functions.

Figure 11 Protein–protein interaction of the overlapping genes between the predicted target genes of miR-144-3p and the NLP analysis.

Notes: The protein-to-protein network analysis of the 119 overlapping genes of the predicted targets of miR-144-3p, the NLP analysis and the differential expression genes of HCC in TCGA were performed in the STRING website. The nodes represent proteins, and each color corresponds to a cluster. The edges indicate the predicted functional associations, which are colored according to the types of predicted associations using different sets of evidence. The red lines, green lines, blue lines, purple lines, yellow lines, light blue lines and black lines indicate fusion evidence, neighborhood evidence, co-occurrence evidence, experimental evidence, text-mining evidence, database evidence and co-expression evidence, respectively. The line thickness indicates the strength of the evidence.
Abbreviations: HCC, hepatocellular carcinoma; NLP, natural language processing; TCGA, The Cancer Genome Atlas.

Table 4 Pathway enrichment in KEGG databases of the targets of miR-144-3p obtained from the predicted target genes, the NLP analysis and the TCGA data

Title	Count	P-value	Genes
hsa05200: pathways in cancer	18	3.73E-08	AR, RET, MAP2K1, PTGS2, FOXO1, KITLG, GLI2, MMP1, CCNE2, CCNE1, FOS, ITGA6, CDKN2B, JUN, SLC2A1, PDGFRA, AXIN2, FIGF
hsa04115: p53 signaling pathway	6	8.31E-04	CCNE2, CCNB1, CCNE1, CCND2, CHEK1, THBS1
hsa04110: cell cycle	7	2.32E-03	CCNE2, CCNB1, CCNE1, CDKN2B, CCND2, CHEK1, MCM6
hsa05215: prostate cancer	6	2.78E-03	CCNE2, CCNE1, AR, MAP2K1, PDGFRA, FOXO1
hsa04510: focal adhesion	8	6.08E-03	MAP2K1, ITGA6, CCND2, JUN, PDGFRA, THBS1, FIGF, SRC
hsa05219: bladder cancer	4	1.07E-02	MAP2K1, THBS1, FIGF, MMP1
hsa05222: small cell lung cancer	5	1.33E-02	CCNE2, CCNE1, PTGS2, CDKN2B, ITGA6
hsa05210: colorectal cancer	5	1.33E-02	FOS, MAP2K1, JUN, PDGFRA, AXIN2
hsa04060: cytokine–cytokine receptor interaction	8	2.37E-02	TNFSF11, IL6ST, PDGFRA, IL1B, IL13, KITLG, FIGF, CXCL12
hsa04620: toll-like receptor signaling pathway	5	2.45E-02	FOS, MAP2K1, JUN, IL1B, TLR4
hsa04114: oocyte meiosis	5	3.22E-02	CCNE2, CCNB1, CCNE1, AR, MAP2K1
hsa04610: complement and coagulation cascades	4	3.98E-02	FGG, THBD, FGA, FGB
hsa05211: renal cell carcinoma	4	4.12E-02	MAP2K1, JUN, SLC2A1, FIGF

Notes: The pathway analysis was performed in KEGG database. Thirteen signaling pathways were enriched (P<0.05).

Abbreviations: KEGG, Kyoto Encyclopedia of Genes and Genomes; NLP, natural language processing; TCGA, The Cancer Genome Atlas.

Table 5 Pathway enrichment in Panther database of the targets of miR-144-3p obtained from the predicted target genes, the NLP analysis and the TCGA data

Title	Count	P-value	Genes
P00050: plasminogen activating cascade	4	5.81E-03	FGG, FGA, FGB, MMP1
P00013: cell cycle	4	1.15E-02	CCNE2, CCNB1, CCNE1, CCND2
P00011: blood coagulation	5	1.37E-02	FGG, THBD, FGA, FGB, TFPI2
P00005: angiogenesis	9	3.28E-02	FOS, EPHA7, SFRP1, JUN, TEK, PDGFRA, AXIN2, ANGPT2, SRC

Notes: The pathway analysis was performed in Panther database. Four significant signaling pathways were enriched (P<0.05).

Abbreviations: NLP, natural language processing; TCGA, The Cancer Genome Atlas.