Background
Methods
Patients and samples
RNA isolation and RT-qPCR
Data mining from TCGA
Collection and management of miR-204-5p data
Prediction and analyses of miR-204-5p target genes
Transcription factor prediction
Statistical analysis
Results
Differential expression and clinical characteristics of miR-204-5p in NSCLC
Clinicopathological parameters | n | Relevant expression of miR-204-5p (2−ΔCq) | |||
---|---|---|---|---|---|
Mean ± SD | t/F-value | p-value | |||
Tissue | NSCLC | 125 | 3.6760 ± 1.87670 | -3.507a | 0.001 |
Non-cancer | 125 | 4.6487 ± 2.46888 | |||
Gender | Male | 75 | 4.0067 ± 1.91843 | 2.461 | 0.015 |
Female | 50 | 3.1800 ± 1.71357 | |||
Age (years) | < 60 | 57 | 3.9526 ± 1.81847 | 1.517 | 0.132 |
> = 60 | 68 | 3.4441 ± 1.90650 | |||
Smoke | No | 38 | 4.3368 ± 1.70205 | −0.108 | 0.914 |
Yes | 30 | 4.3833 ± 1.83041 | |||
Histological type | Adenocarcinoma | 101 | 3.4663 ± 1.82397 | −2.902 | 0.004 |
Squamous carcinoma | 23 | 4.6870 ± 1.80638 | |||
Tumor size | <=3 cm | 60 | 3.2417 ± 1.78547 | −2.540 | 0.012 |
> 3 cm | 65 | 4.0769 ± 1.88280 | |||
Vascular invasion | No | 90 | 4.2233 ± 1.68876 | 5.898 | < 0.001 |
Yes | 35 | 2.2686 ± 1.59609 | |||
TNM | I-II | 54 | 4.0870 ± 1.96383 | 2.167 | 0.032 |
III-IV | 71 | 3.3634 ± 1.75770 | |||
Lymph node metastasis | No | 56 | 4.2089 ± 1.95897 | 2.948 | 0.004 |
Yes | 69 | 3.2435 ± 1.70142 | |||
Pathological grading | I | 17 | 4.2176 ± 1.94140 | 2.797b | 0.065 |
II | 78 | 3.8090 ± 1.85404 | |||
III | 30 | 3.6760 ± 1.87670 |
Clinicopathological parameters | n | Relevant expression of miR-204-5p (2−ΔCq) | |||
---|---|---|---|---|---|
Mean ± SD | t/F-value | p-value | |||
Tissue | LUAD | 101 | 3.4663 ± 1.82397 | -2.731a | 0.007 |
Non-cancer | 101 | 4.2786 ± 2.36824 | |||
Gender | Male | 56 | 3.7768 ± 1.91937 | 1.934 | 0.056 |
Female | 45 | 3.0800 ± 1.63729 | |||
Age (years) | < 60 | 41 | 3.7390 ± 1.85039 | 1.245 | 0.216 |
> = 60 | 60 | 3.2800 ± 1.79734 | |||
Smoke | No | 26 | 4.1000 ± 1.67141 | −0.695 | 0.491 |
Yes | 18 | 4.4611 ± 1.72768 | |||
Tumor size | <=3 cm | 53 | 3.0906 ± 1.72362 | −2.218 | 0.029 |
> 3 cm | 48 | 3.8813 ± 1.85915 | |||
Vascular invasion | No | 70 | 4.1114 ± 1.63215 | 6.286 | < 0.001 |
Yes | 31 | 2.0097 ± 1.34123 | |||
TNM | I-II | 44 | 3.8864 ± 1.87190 | 2.066 | 0.041 |
III-IV | 57 | 3.1421 ± 1.73339 | |||
Lymph node metastasis | No | 45 | 4.0556 ± 1.86822 | 3.027 | 0.003 |
Yes | 56 | 2.9929 ± 1.65660 | |||
Pathological grading | I | 17 | 4.2176 ± 1.94140 | 5.477b | 0.006 |
II | 61 | 3.6279 ± 1.81752 | |||
III | 23 | 2.4826 ± 1.36070 |
Clinicopathological parameters | n | Relevant expression of miR-204-5p (2−ΔCq) | |||
---|---|---|---|---|---|
Mean ± SD | t/F-value | p-value | |||
Tissue | LUSC | 23 | 4.6870 ± 1.80638 | -2.264a | 0.029 |
Non-cancer | 23 | 6.0217 ± 2.17547 | |||
Gender | Male | 18 | 4.8556 ± 1.68041 | 0.844 | 0.408 |
Female | 5 | 4.0800 ± 2.31452 | |||
Age (years) | < 60 | 15 | 4.6933 ± 1.52572 | 0.020 | 0.985 |
> = 60 | 8 | 4.6750 ± 2.36628 | |||
Smoke | No | 12 | 4.8500 ± 1.72495 | 0.444 | 0.662 |
Yes | 11 | 4.5091 ± 1.95931 | |||
Tumor size | <=3 cm | 7 | 4.3857 ± 1.96759 | −0.520 | 0.608 |
> 3 cm | 16 | 4.8188 ± 1.78222 | |||
Vascular invasion | No | 20 | 4.6150 ± 1.86471 | −0.485 | 0.633 |
Yes | 3 | 5.1667 ± 1.56950 | |||
TNM | I-II | 10 | 4.9700 ± 2.21512 | 0.650 | 0.523 |
III-IV | 13 | 4.4692 ± 1.47783 | |||
Lymph node metastasis | No | 11 | 4.8364 ± 2.28266 | 0.364 | 0.721 |
Yes | 12 | 4.5500 ± 1.32150 | |||
Pathological grading | I | 0 | 0.038b | 0.848 | |
II | 16 | 4.6375 ± 1.80032 | |||
III | 7 | 4.8000 ± 1.95959 |
Verification of miR-204-5p expression in TCGA
Results of data mining
ID | Lead author | Year | Country | Source | Platform | Experimental type | Citation | Cancer No. | Control No. | T value | Pvalue |
---|---|---|---|---|---|---|---|---|---|---|---|
GSE16512 | Lodes MJ | 2009 | USA | plasma | GPL8686 | array | [31] | 3 | 14 | 0.066 | 0.057 |
GSE17681 | Keller A | 2009 | Germany | plasma | GPL9040 | array | [32] | 17 | 19 | −1.104 | 0.009 |
GSE24709 | Keller A | 2011 | Germany | plasma | GPL9040 | array | [33] | 28 | 19 | 2.289 | 0.000 |
GSE27486 | Patnaik SK | 2010 | USA | plasma | GPL11432 | array | [34] | 22 | 23 | 1.699 | 0.518 |
GSE31568 | Keller A | 2011 | Germany | plasma | GPL9040 | array | [35] | 32 | 70 | 1.527 | 0.363 |
GSE40738 | Patnaik SK | 2012 | USA | plasma | GPL16016 | array | [36] | 86 | 59 | −2.561 | 0.125 |
GSE46729 | Godrey A | 2014 | USA | plasma | GPL8786 | array | [37] | 24 | 24 | 0.955 | 0.945 |
GSE61741 | Keller A | 2014 | Germany | plasma | GPL9040 | array | [38] | 73 | 94 | 4.427 | 0.000 |
GSE68951 | Leidinger P | 2015 | Germany | plasma | GPL16770 | array | [39] | 26 | 12 | 2.553 | 0.773 |
PMID:26497897 | Guo W | 2015 | China | plasma | NR | RT-qPCR | [15] | 126 | 50 | NR | < 0.001 |
GSE93300 | Liu X | 2017 | China | plasma | GPL21576 | array | [40] | 9 | 4 | 3.557 | 0.748 |
GSE2564 | Lu J | 2005 | USA | tissue | GPL1987 | array | [41] | 14 | 4 | −0.731 | 0.396 |
GSE14936 | Seike M | 2009 | USA | tissue | GPL8879 | array | [42] | 26 | 26 | −1.344 | 0.654 |
GSE15008 | Tan X | 2009 | China | tissue | GPL8176 | array | [43] | 187 | 174 | 2.883 | 0.000 |
GSE16025 | Raponi M | 2009 | USA | tissue | GPL5106 | array | [44] | 61 | 10 | 0.916 | 0.111 |
GSE18692 | Puissegur M | 2009 | France | tissue | GPL4718 | array | [45] | 13 | 13 | −5.072 | 0.617 |
GSE19945 | Ohba T | 2010 | Japan | tissue | GPL9948 | array | [46] | 20 | 8 | −1.305 | 0.289 |
GSE25508 | Guled M | 2011 | Finland | tissue | GPL7731 | array | [47] | 26 | 26 | 1.868 | 0.080 |
GSE29248 | Ma L | 2010 | China | tissue | GPL8179 | array | [48] | 6 | 6 | −0.431 | 0.474 |
GSE36681 | Jang JS | 2012 | USA | tissue | GPL8179 | array | [49] | 103 | 103 | −3.282 | 0.001 |
GSE47525 | van Jaarsveld MT | 2013 | Netherlands | tissue | GPL17222 | array | [50] | 18 | 14 | −1.499 | 0.103 |
GSE48414 | Bjaanaes MM | 2014 | Norway | tissue | GPL16770 | array | [51] | 154 | 20 | −5.891 | 0.000 |
GSE51853 | Arima C | 2014 | Japan | tissue | GPL7341 | array | [52] | 126 | 5 | −1.63 | 0.103 |
GSE53882 | Pu HY | 2014 | China | tissue | GPL18130 | array | [53] | 397 | 151 | 0.148 | 0.933 |
GSE56036 | Fujita Y | 2014 | Japan | tissue | GPL15446 | array | [54] | 14 | 27 | −0.756 | 0.204 |
GSE63805 | Robles AI | 2014 | USA | tissue | GPL18410 | array | [55] | 32 | 30 | 0.449 | 0.074 |
GSE72526 | Gasparini P | 2015 | Switzerland | tissue | GPL20275 | array | [56] | 67 | 18 | − 3.904 | 0.000 |
GSE74190 | Jin Y | 2015 | China | tissue | GPL19622 | array | [57] | 72 | 44 | −1.306 | 0.141 |
GSE102286 | Mitchell KA | 2017 | USA | tissue | GPL23871 | array | [58] | 91 | 88 | −1.087 | 0.003 |
TCGA | NR | NR | NR | tissue | NR | array | NR | 999 | 91 | −3.055 | 0.000 |
Literature 1 | Li LX | 2017 | China | tissue | NR | RT-qPCR | [28] | 39 | 39 | NR | <0.01 |
Literature 2 | Xu YZ | 2018 | China | tissue | NR | RT-qPCR | [30] | 60 | 60 | 9.361 | 0.000 |
Literature 3 | Wang QC | 2018 | China | tissue | NR | RT-qPCR | [29] | 72 | 72 | 11.028 | <0.01 |
Current study | NR | NR | China | tissue | NR | RT-qPCR | NR | 125 | 125 | −3.507 | 0.007 |
Integrated meta-analyses of miR-204-5p datasets in NSCLC
Clinical role of miR-204-5p in NSCLC
ID | Author | Year | Country | Source | Citation | Cases/Controls No. | AUC | Threshold | Sensitivity | Specificity | TP | FP | FN | TN |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
GSE16512 | Lodes MJ | 2009 | USA | plasma | [31] | 3/14 | 0.536 | −0.133 | 0.667 | 0.643 | 2 | 5 | 1 | 9 |
GSE17681 | Keller A | 2009 | Germany | plasma | [32] | 17/19 | 0.562 | 4.346 | 0.941 | 0.316 | 16 | 13 | 1 | 6 |
GSE24709 | Keller A | 2011 | Germany | plasma | [33] | 28/19 | 0.348 | 6.960 | 0.964 | 0.000 | 27 | 19 | 1 | 0 |
GSE27486 | Patnaik SK | 2010 | USA | plasma | [34] | 22/23 | 0.360 | −0.025 | 0.045 | 0.957 | 1 | 1 | 21 | 22 |
GSE31568 | Keller A | 2011 | Germany | plasma | [35] | 32/70 | 0.409 | 5.016 | 0.875 | 0.816 | 28 | 57 | 4 | 13 |
GSE40738 | Patnaik SK | 2012 | USA | plasma | [36] | 86/59 | 0.582 | −0.085 | 0.953 | 0.237 | 82 | 45 | 4 | 14 |
GSE46729 | Godrey A | 2014 | USA | plasma | [37] | 24/24 | 0.434 | 4.193 | 0.417 | 0.667 | 10 | 8 | 14 | 16 |
GSE61741 | Keller A | 2014 | Germany | plasma | [38] | 73/94 | 0.346 | 6.828 | 1.000 | 0.011 | 73 | 93 | 0 | 1 |
GSE68951 | Leidinger P | 2015 | Germany | plasma | [39] | 26/12 | 0.212 | 3.575 | 0.923 | 0.083 | 24 | 11 | 2 | 1 |
PMID:26497897 | Guo W | 2015 | China | plasma | [15] | 126/50 | 0.809 | 0.023 | 0.760 | 0.820 | 96 | 9 | 30 | 41 |
GSE93300 | Liu X | 2017 | China | plasma | [40] | 9/4 | 0.056 | −3.499 | 1.000 | 0.000 | 9 | 4 | 0 | 0 |
GSE2564 | Lu J | 2005 | USA | tissue | [41] | 14/4 | 0.741 | 5.835 | 0.786 | 0.750 | 11 | 1 | 3 | 3 |
GSE14936 | Seike M | 2009 | USA | tissue | [42] | 26/26 | 0.607 | 8.545 | 0.500 | 0.731 | 13 | 7 | 13 | 19 |
GSE15008 | Tan X | 2009 | China | tissue | [43] | 187/174 | 0.447 | 7.941 | 0.294 | 0.776 | 55 | 39 | 132 | 135 |
GSE16025 | Raponi M | 2009 | USA | tissue | [44] | 61/10 | 0.454 | 4.813 | 0.131 | 1.000 | 8 | 0 | 53 | 10 |
GSE18692 | Puissegur M | 2009 | France | tissue | [45] | 13/13 | 0.917 | −0.076 | 0.846 | 0.923 | 11 | 1 | 2 | 12 |
GSE19945 | Ohba T | 2010 | Japan | tissue | [46] | 20/8 | 0.769 | −0.342 | 0.700 | 0.875 | 14 | 1 | 6 | 7 |
GSE25508 | Guled M | 2011 | Finland | tissue | [47] | 26/26 | 0.348 | 9.004 | 1.000 | 0.000 | 26 | 26 | 0 | 0 |
GSE29248 | Ma L | 2010 | China | tissue | [48] | 6/6 | 0.583 | 10.704 | 0.833 | 0.500 | 5 | 3 | 1 | 3 |
GSE36681 | Jang JS | 2012 | USA | tissue | [49] | 103/103 | 0.619 | 10.847 | 0.845 | 0.417 | 87 | 60 | 16 | 43 |
GSE47525 | van Jaarsveld MT | 2013 | Netherlands | tissue | [50] | 18/14 | 0.661 | 2.755 | 0.389 | 0.929 | 7 | 1 | 11 | 13 |
GSE48414 | Bjaanaes MM | 2014 | Norway | tissue | [51] | 154/20 | 0.900 | 1.503 | 0.825 | 0.900 | 127 | 2 | 27 | 18 |
GSE51853 | Arima C | 2014 | Japan | tissue | [52] | 126/5 | 0.821 | −4.558 | 0.659 | 1.000 | 83 | 0 | 43 | 5 |
GSE53882 | Pu HY | 2014 | China | tissue | [53] | 397/151 | 0.521 | 0.965 | 0.554 | 0.589 | 220 | 62 | 177 | 89 |
GSE56036 | Fujita Y | 2014 | Japan | tissue | [54] | 14/27 | 0.574 | 3.960 | 0.929 | 0.333 | 13 | 18 | 1 | 9 |
GSE63805 | Robles AI | 2014 | USA | tissue | [55] | 32/30 | 0.468 | 1.443 | 0.250 | 0.933 | 8 | 2 | 24 | 28 |
GSE72526 | Gasparini P | 2015 | Switzerland | tissue | [56] | 67/18 | 0.786 | 1.793 | 0.731 | 0.833 | 49 | 3 | 18 | 15 |
GSE74190 | Jin Y | 2015 | China | tissue | [57] | 72/44 | 0.620 | 0.472 | 0.583 | 0.705 | 42 | 13 | 30 | 31 |
GSE102286 | Mitchell KA | 2017 | USA | tissue | [58] | 91/88 | 0.503 | −0.529 | 0.714 | 0.443 | 65 | 49 | 26 | 39 |
TCGA | NR | NR | NR | tissue | NR | 999/91 | 0.671 | 1.657 | 0.520 | 0.901 | 519 | 9 | 480 | 82 |
Current study | NR | NR | China | tissue | NR | 125/125 | 0.613 | 2.350 | 0.320 | 0.864 | 40 | 17 | 85 | 108 |
Sample type | Study number | Enrolled number | AUC | Overall estimate | Heterogeneity | Pretest probability | ||||
---|---|---|---|---|---|---|---|---|---|---|
95% CI (LL-UL) | sensitivity | specificity | Q | I2 (%) | Phet | |||||
Overall | 31 | 4368 | 0.74 | 0.70–0.77 | 0.76 | 0.58 | 864.488 | 99.77 | 0.000 | 0.686 |
Tissue | 20 | 3534 | 0.75 | 0.71–0.78 | 0.65 | 0.74 | 328.601 | 99.39 | 0.000 | 0.722 |
Plasma | 11 | 834 | 0.70 | 0.66–0.74 | 0.90 | 0.27 | 279.536 | 99.28 | 0.000 | 0.535 |
LUAD | 7 | 1269 | 0.78 | 0.74–0.81 | 0.63 | 0.78 | 150.286 | 98.67 | 0.000 | 0.742 |
LUSC | 4 | 1001 | 0.66 | 0.62–0.70 | 0.32 | 0.90 | 3.112 | 35.72 | 0.106 | 0.748 |
LUAD-tissue | 5 | 1211 | 0.79 | 0.75–0.82 | 0.61 | 0.81 | 106.761 | 98.13 | 0.000 | 0.752 |
Prognostic evaluation of miR-204-5p in NSCLC
ID | Author | Year | Country | Sample type | Citation | Cutoff | Method | Survival type | Sample size | HR | LL | UL |
---|---|---|---|---|---|---|---|---|---|---|---|---|
GSE16025 | Raponi M | 2009 | USA | tissue | [44] | median | Univariate analysis | OS | 61 | 1.322 | 0.675 | 2.590 |
GSE63805 | Robles AI | 2014 | USA | tissue | [55] | median | Univariate analysis | OS | 32 | 2.060 | 0.951 | 4.463 |
PMID:25412236 | Shi L | 2014 | China | tissue | [59] | median | Kaplan–Meier analysis | OS | 48 | 1.770 | 0.790 | 3.950 |
PMID:26497897 | Guo W | 2015 | China | plasma | [15] | median | Univariate analysis | OS | 126 | 1.936 | 1.193 | 3.143 |
GSE102286 | Mitchell KA | 2017 | USA | tissue | [58] | median | Univariate analysis | OS | 91 | 0.776 | 0.495 | 1.215 |
Current study | NR | NR | China | tissue | NR | median | Univariate analysis | OS | 57 | 0.640 | 0.306 | 1.340 |
Screening and validation of miR-204-5p target genes
Category | ID | Term | Count | % | P value | Genes |
---|---|---|---|---|---|---|
BP | GO:0001764 | neuron migration | 13 | 0.015581 | 3.06E-06 | PHOX2B, NDE1, SATB2, CDK5R1, CDK5R2, NAV1, SOX1, NTRK2, CELSR3, NEUROD4, DCX, FBXO45, PITX2 |
BP | GO:0051965 | positive regulation of synapse assembly | 8 | 0.009588 | 4.35E-04 | SLITRK1, SRPX2, NTRK2, IL1RAP, EFNA5, TPBG, EPHB1, EPHB2 |
BP | GO:0008284 | positive regulation of cell proliferation | 17 | 0.020375 | 6.96E-04 | CDC7, FGF5, HMX2, E2F3, RARG, PKHD1, SOX4, GREM1, EPHA1, GDNF, IL11, HDAC1, TFAP2B, POU3F2, EIF5A2, DPP4, DLG1 |
CC | GO:0043005 | neuron projection | 12 | 0.014382 | 2.91E-04 | TENM4, TENM1, KIF5A, STMN2, SLC6A2, OPRK1, BCL11B, KIF5C, STMN4, GABBR2, DCX, CALB1 |
CC | GO:0005887 | integral component of plasma membrane | 38 | 0.045544 | 7.23E-04 | GPR83, SLC5A3, SLC13A5, SLC20A2, SLC6A2, OPRK1, LRRC8D, GNRHR, CNGB3, SLC52A3, LGR4, EPHB1, EPHB2, EPCAM, ADRA2A, HCN3, HCN1, SLC12A7, GABRG2, CLCA2, RET, SLC6A17, MMP15, EPHA1, GRM1, SLC7A11, TIGIT, TENM4, EPHA7, SLC16A7, TMPRSS11D, TENM1, SLC6A8, SLC17A4, NTRK2, CLDN1, KCNH8, HAS3 |
CC | GO:0005667 | transcription factor complex | 12 | 0.014382 | 0.005459 | E2F3, SATB2, BARX2, RARG, HNF1A, TRPS1, SIX1, TP63, POU3F2, TBL1X, TP73, PITX2 |
MF | GO:0005248 | voltage-gated sodium channel activity | 5 | 0.005993 | 5.84E-04 | HCN1, SCN8A, SCN5A, HCN3, SCN4A |
MF | GO:0005249 | voltage-gated potassium channel activity | 7 | 0.00839 | 8.94E-04 | HCN1, KCNQ5, KCNH8, KCNA7, HCN3, CNGB3, KCNE4 |
MF | GO:0001077 | transcriptional activator activity, RNA polymerase II core promoter proximal region sequence-specific binding | 15 | 0.017978 | 0.001203 | PHOX2B, FOXL2, SOX1, ONECUT2, SOX4, TP63, SIX2, HLTF, TP73, HOXC11, BCL11B, SIX1, TFAP2B, TFAP2A, POU3F2 |
KEGG | cfa05206 | MicroRNAs in cancer | 10 | 0.011985 | 0.005364 | E2F1, DNMT3A, E2F3, WNT3, MMP9, IGF2BP1, TP63, CDK6, MMP16, HMGA2 |
KEGG | cfa04514 | Cell adhesion molecules (CAMs) | 8 | 0.009588 | 0.039758 | TIGIT, SDC1, CLDN19, CLDN1, CNTNAP2, VCAN, NRXN1, CDH2 |
KEGG | cfa04550 | Signaling pathways regulating pluripotency of stem cells | 8 | 0.009588 | 0.04251 | DVL3, FZD10, WNT3, HNF1A, INHBE, JARID2, NEUROG1, JAK3 |
TFs and the miR-204-5p regulatory network
Gene | TF name | Score | Relative score | Start | End | Strand | Predicted sequence |
---|---|---|---|---|---|---|---|
miR-204-5p | MAX | 6.92367 | 0.811791 | 21 | 30 | + | TGACTCGTGG |
DLG1 | MAX | 8.54191 | 0.861233 | 2277 | 2286 | + | AAACAAGTGA |
RUNX1 | 7.92698 | 0.834755 | 2446 | 2456 | + | TTATGAGGTAG | |
EPHB2 | MAX | 10.4915 | 0.928629 | 402 | 411 | + | TCCACGTGGA |
MYC | 11.9965 | 0.918300 | 401 | 412 | + | ATCCACGTGGAG | |
GDNF | MAX | 6.56373 | 0.800793 | 116 | 125 | + | AGTCTCGTGC |
MYC | 6.37509 | 0.800941 | 116 | 127 | + | AGTCTCGTGCTC | |
RUNX1 | 10.8526 | 0.910532 | 1943 | 1953 | + | AGTTGTGGTTT |