Diagnostic value of circular RNAs as effective biomarkers for cancer: a systematic review and meta-analysis

Figures & data

Figure 1 Flow diagram of the study selection process.

Table 1 Main characteristics of the studies included in the meta-analysis

Author	Year	circRNAs profiles	Cancer type	Specimen	Test method	Sample size (case/control)	Sensitivity	Specificity
Li et al.^Citation8	2017	hsa_circ_0000096	GC	Tissues	qRT–PCR	101/101	0.880	0.560
Zhu et al.^Citation9	2017	hsa_circ_0013958	LAC	Tissues	qRT–PCR	49/49	0.755	0.796
		hsa_circ_0013958	LAC	Plasma	qRT–PCR	30/30	0.667	0.933
Yin et al.^Citation10	2017	hsa_circ_0001785	BC	Plasma	qRT–PCR	20/20	0.786	0.756
		hsa_circ_0108942	BC	Plasma	qRT–PCR	20/20	0.815	0.504
		hsa_circ_0068033	BC	Plasma	qRT–PCR	20/20	0.732	0.578
Zhao et al.^Citation11	2017	hsa_circ_0000181	GC	Tissues	qRT–PCR	115/115	0.539	0.852
		hsa_circ_0000181	GC	Plasma	qRT–PCR	102/105	0.990	0.206
Fu et al.^Citation12	2017	hsa_circ_0003570	HCC	Tissues	qRT–PCR	107/107	0.449	0.868
Li et al.^Citation13	2017	hsa circ 0001649	GC	Tissues	qRT–PCR	76/76	0.711	0.816
Qin et al.^Citation14	2015	hsa_circ_0001649	HCC	Tissues	qRT–PCR	89/89	0.810	0.690
Wang et al.^Citation15	2015	hsa_circ_001988	CRC	Tissues	qRT–PCR	31/31	0.680	0.730
Yao et al.^Citation16	2017	circZKSCAN1	HCC	Tissues	qRT–PCR	102/102	0.822	0.724
Zhuo et al.^Citation17	2017	circRNA0003906	CRC	Tissues	qRT–PCR	122/40	0.725	0.803
Li et al.^Citation18	2017	hsa_circ_0001017	GC	Plasma	qRT–PCR	121/121	0.974	0.811
		hsa_circ_0061276	GC	Plasma	qRT–PCR	121/121	0.903	0.517
Shang et al.^Citation19	2016	hsa_circ_0005075	HCC	Tissues	qRT–PCR	30/30	0.833	0.900
Li et al.^Citation20	2015	hsa_circ_002059	GC	Tissues	qRT–PCR	101/101	0.810	0.620
Chen et al.^Citation21	2017	hsa_circ_0000190	GC	Tissues	qRT–PCR	104/104	0.721	0.683
		hsa_circ_0000190	GC	Plasma	qRT–PCR	104/104	0.414	0.875
Huang et al.^Citation22	2017	hsa_circ_0000745	GC	Plasma	qRT–PCR	60/60	0.855	0.450
Lu et al.^Citation23	2017	hsa_circ_0006633	GC	Tissues	qRT–PCR	96/96	0.600	0.810
Sun et al.^Citation24	2017	hsa_circ_0000520	GC	Tissues	qRT–PCR	56/56	0.536	0.857
		hsa_circ_0000521	GC	Plasma	qRT–PCR	45/17	0.824	0.844
Tian et al.^Citation25	2017	hsa_circ_0003159	GC	Tissues	qRT–PCR	108/108	0.852	0.565
Lu et al.^Citation26	2018	hsa_circ_0000467	GC	Plasma	qRT–PCR	20/20	0.705	0.648
Zhang et al.^Citation27	2018	hsa_circ_0091579	HCC	Tissues	qRT–PCR	30/30	0.970	0.400
		hsa_circ_16245-1	HCC	Tissues	qRT–PCR	30/30	0.830	0.630
Shao et al.^Citation28	2017	hsa_circ_0001895	GC	Tissues	qRT–PCR	96/96	0.678	0.857
Wang et al.^Citation29	2017	hsa_circ_0000567	CRC	Tissues	qRT–PCR	102/102	0.833	0.765
Zhao et al.^Citation30	2018	hsa_circ_0081001	OSCC	Salivary	qRT–PCR	90/82	0.744	0.902
Fu,et al.^Citation31	2017	hsa_circ_0004018	HCC	Tissues	qRT–PCR	102/102	0.716	0.815

Abbreviations: GC, gastric cancer; BC, breast cancer; HCC, hepatocellular carcinoma; CRC, colorectal cancer; LAC, lung adenocarcinoma; OSCC, oral squamous cell carcinoma; qRT-PCR, quantitative reverse transcription PCR.

Figure 2 Quality assessment of the included studies according to QUADAS-2.

Figure 3 Forest plots of sensitivity and specificity of circRNAs for cancer diagnosis. (A) Pooled sensitivity for circRNAs. (B) Pooled specificity for circRNAs.

Figure 4 Summary receiver operator characteristic curve for cancer diagnosis.

Table 2 Results of subgroup analysis

Subgroups	Studies	Sensitivity [95% CI]	Specificity [95% CI]	PLR [95% CI]	NLR [95% CI]	DOR [95% CI]	AUC [95% CI]
Specimen
Tissue	20	0.75[0.69–0.80]	0.75[0.69–0.80]	3.0[2.6–3.5]	0.33[0.28–0.40]	9[7–11]	0.81[0.78–0.85]
Other	12	0.84[0.72–0.91]	0.70[0.56–0.82]	2.8[1.9–4.2]	0.23[0.14–0.38]	12[7–23]	0.84[0.81–0.87]
Case size
≥100	17	0.82[0.72–0.89]	0.70[0.61–0.78]	2.8[2.2–3.5]	0.25[0.17–0.37]	11[8–16]	0.82[0.79–0.85]
<100	15	0.74[0.69–0.79]	0.77[0.69–0.83]	3.2[2.4–4.2]	0.34[0.28–0.40]	10[7–13]	0.81[0.77–0.84]
Cancer type
GC	16	0.80[0.69–0.87]	0.71[0.61–0.79]	2.7[2.1–3.5]	0.29[0.20–0.41]	9[6–14]	0.81[0.78–0.85]
Other	16	0.78[0.71–0.83]	0.76[0.70–0.82]	3.3[2.6–4.0]	0.29[0.24–0.37]	11[8–15]	0.84[0.80–0.87]
Overall	32	0.79[0.73–0.84]	0.73[0.67–0.79]	2.9[2.5–3.5]	0.29[0.24–0.36]	10[8–13]	0.83[0.79–0.86]

Abbreviations: GC, gastric cancer; PLR, positive likelihood ratio; NLR, negative likelihood ratio; DOR, diagnostic odd ratio; AUC, area under the curve.

Figure 5 Subgroup analyses according to cancer type.

Figure 6 Sensitivity analysis of the overall pooled study.

Figure 7 Deeks’ funnel plot to assess publication bias.

Abbreviation: ESS, effective sample size.

Li P, Chen H, Chen S, et al. Circular RNA 0000096 affects cell growth and migration in gastric cancer. Br J Cancer. 2017;116(5):626–633. doi:10.1038/bjc.2016.45128081541

 PubMed Web of Science ®Google Scholar

Zhu X, Wang X, Wei S, et al. hsa_circ_0013958: a circular RNA and potential novel biomarker for lung adenocarcinoma. FEBS J. 2017;284(14):2170–2182. doi:10.1111/febs.1413228685964

 PubMed Web of Science ®Google Scholar

Yin WB, Yan MG, Fang X, Guo JJ, Xiong W, Zhang RP. Circulating circular RNA hsa_circ_0001785 acts as a diagnostic biomarker for breast cancer detection. Clin Chim Acta. 2018;487:363–368. doi:10.1016/j.cca.2017.10.01129045858

 PubMed Web of Science ®Google Scholar

Zhao Q, Chen S, Li T, Xiao B, Zhang X. Clinical values of circular RNA 0000181 in the screening of gastric cancer. J Clin Lab Anal. 2018;32(4):e22333. doi:10.1002/jcla.2018.32.issue-428940688

 PubMed Web of Science ®Google Scholar

Fu L, Wu S, Yao T, et al. Decreased expression of hsa_circ_0003570 in hepatocellular carcinoma and its clinical significance. J Clin Lab Anal. 2018;32(2). doi:10.1002/jcla.22239.

 Web of Science ®Google Scholar

Li WH, Song YC, Zhang H, et al. Decreased expression of Hsa_circ_00001649 in gastric cancer and its clinical significance. Dis Markers. 2017;2017:4587698. doi:10.1155/2017/458769828167847

 PubMed Web of Science ®Google Scholar

Qin M, Liu G, Huo X, et al. Hsa_circ_0001649: A circular RNA and potential novel biomarker for hepatocellular carcinoma. Cancer Biomark. 2016;16(1):161–169. doi:10.3233/CBM-15055226600397

 PubMed Web of Science ®Google Scholar

Wang X, Zhang Y, Huang L, et al. Decreased expression of hsa_circ_001988 in colorectal cancer and its clinical significances. Int J Clin Exp Pathol. 2015;8(12):16020–16025.26884878

 PubMed Web of Science ®Google Scholar

Yao Z, Luo J, Hu K, et al. ZKSCAN1 gene and its related circular RNA (circZKSCAN1) both inhibit hepatocellular carcinoma cell growth, migration, and invasion but through different signaling pathways. Mol Oncol. 2017;11(4):422–437. doi:10.1002/1878-0261.1204528211215

 PubMed Web of Science ®Google Scholar

Zhuo F, Lin H, Chen Z, Huang Z, Hu J. The expression profile and clinical significance of circRNA0003906 in colorectal cancer. Onco Targets Ther. 2017;10:5187–5193. doi:10.2147/OTT.S14737829123417

 PubMed Web of Science ®Google Scholar

Li T, Shao Y, Fu L, et al. Plasma circular RNA profiling of patients with gastric cancer and their droplet digital RT-PCR detection. J Mol Med (Berl). 2018;96(1):85–96. doi:10.1007/s00109-017-1600-y29098316

 PubMed Web of Science ®Google Scholar

Shang X, Li G, Liu H, et al. Comprehensive circular RNA profiling reveals that hsa_circ_0005075, a new circular RNA biomarker, is involved in hepatocellular crcinoma development. Medicine. 2016;95(22):e3811. doi:10.1097/MD.000000000000486427258521

 PubMed Web of Science ®Google Scholar

Li P, Chen S, Chen H, et al. Using circular RNA as a novel type of biomarker in the screening of gastric cancer. Clin Chim Acta. 2015;444:132–136. doi:10.1016/j.cca.2015.02.01825689795

 PubMed Web of Science ®Google Scholar

Chen S, Li T, Zhao Q, Xiao B, Guo J. Using circular RNA hsa_circ_0000190 as a new biomarker in the diagnosis of gastric cancer. Clin Chim Acta. 2017;466:167–171. doi:10.1016/j.cca.2017.01.02528130019

 PubMed Web of Science ®Google Scholar

Huang M, He YR, Liang LC, Huang Q, Zhu ZQ. Circular RNA hsa_circ_0000745 may serve as a diagnostic marker for gastric cancer. World J Gastroenterol. 2017;23(34):6330–6338. doi:10.3748/wjg.v23.i34.633028974900

 PubMed Web of Science ®Google Scholar

Lu R, Shao Y, Ye G, Xiao B, Guo J. Low expression of hsa_circ_0006633 in human gastric cancer and its clinical significances. Tumour Biol. 2017;39(6):1010428317704175. doi:10.1177/101042831770417528656881

 PubMedGoogle Scholar

Sun H, Tang W, Rong D, et al. Hsa_circ_0000520, a potential new circular RNA biomarker, is involved in gastric carcinoma. Cancer Biomark. 2018;21(2):299–306. doi:10.3233/CBM-17037929103021

 PubMed Web of Science ®Google Scholar

Tian M, Chen R, Li T, Xiao B. Reduced expression of circRNA hsa_circ_0003159 in gastric cancer and its clinical significance. J Clin Lab Anal. 2018;32(3):e22281. doi:10.1002/jcla.2018.32.issue-3

 PubMed Web of Science ®Google Scholar

Lu J, Zhang PY, Xie JW. et al. Hsa_circ_0000467 promotes cancer progression and serves as a diagnostic and prognostic biomarker for gastric cancer. J Clin Lab Anal;2018:e22726. doi:10.1002/jcla.2272630461077

 PubMed Web of Science ®Google Scholar

Zhang C, Zhang C, Lin J, Wang H. Circular RNA Hsa_Circ_0091579 serves as a diagnostic and prognostic marker for hepatocellular carcinoma. Cell Physiol Biochem. 2018;51(1):290–300. doi:10.1159/00049523030453307

 PubMedGoogle Scholar

Shao Y, Chen L, Lu R, et al. Decreased expression of hsa_circ_0001895 in human gastric cancer and its clinical significances. Tumour Biol. 2017;39(4):1010428317699125. doi:10.1177/101042831769912528443463

 PubMedGoogle Scholar

Wang J, Li X, Lu L, He L, Hu H, Xu Z. Circular RNA hsa_circ_0000567 can be used as a promising diagnostic biomarker for human colorectal cancer. J Clin Lab Anal. 2018;32(5):e22379. doi:10.1002/jcla.2018.32.issue-529333615

 PubMed Web of Science ®Google Scholar

Zhao SY, Wang J, Ouyang SB, Huang ZK, Liao L. Salivary circular RNAs Hsa_Circ_0001874 and Hsa_Circ_0001971 as novel biomarkers for the diagnosis of oral squamous cell carcinoma. Cell Physiol Biochem. 2018;47(6):2511–2521. doi:10.1159/00049162429991057

 PubMedGoogle Scholar

Fu L, Yao T, Chen Q, Mo X, Hu Y, Guo J. Screening differential circular RNA expression profiles reveals hsa_circ_0004018 is associated with hepatocellular carcinoma. Oncotarget. 2017;8(35):58405–58416. doi:10.18632/oncotarget.1688128938566

 PubMedGoogle Scholar