Plasma cell-free circRNAs panel act as fingerprint predicts the occurrence of laryngeal squamous cell carcinoma

The circRNA expression profile in LSCC and control group

The analysis of circRNA microarray indicted that the cluster diagram showed the circRNA lineages with abnormal differentially expressed circRNAs among each group, while the circRNAs with statistically significant differences among each group were presented by the volcano diagram (Figure 1A). Due to the spatio-temporal characteristics of circRNA expression, we set a specific threshold to ensure the feasibility of subsequent validation. The expression level of circRNA in the chip must meet a clear statistical significance (P < 0.05), and the detectable rate in the chip must be greater than 75%. Under the limitation of the above criteria, we found that compared with the control group, 122 circRNAs transcriptome specificity was increased in the LSCC group, and 98 circRNAs were confirmed to be down-regulated (Figure 1B). In order to reveal the potential biomarker for LSCC, we selected the top 20 increased circRNAs in LSCC group as candidate diagnostic makers (Figure 1C).

Validation of significantly dysregulated circRNAs in plasma

Two staged validation of candidate circRNAs was used including 20 paired samples as training set and 100 paired samples as validation set. The detailed information of patients and healthy controls was summarized in Table 1. A randomly selected 20 paired LSCC and control samples was used. The top 20 circRNAs was first validated. Among the 20 candidate circRNAs, 10 circRNAs was confirmed with significant different expression; however, 5 circRNAs was consistent with microarray results while the rest circRNAs was presented with decreased level in LSCC group.

Based on the results in training set, the rest 100 paired samples were enrolled as validation set. We next examine the expression of the five candidate circRNAs in validation set. We found that hsa_circ_0055202, hsa_circ_0074920 and hsa_circ_0043722 was confirmed with higher expression level in LSCC, while hsa_circ_0010178 presented no significant. The hsa_circ_0009760 presented a higher expression in LSCC; however, the p value was <0.05.

Two-stage validation of candidate circRNAs was performed, with 20 pairs of paired samples as the training set and 100 pairs as the validation set. As shown in Figure 2A, 20 pairs of LSCC and control samples were randomly selected. The top 20 circRNAs were identified for the first time. Among the 20 candidate circRNAs, three circRNAs entitled circ_0019201, circ_0011773 and circ_0122790 were proved to be differentially expressed and consistent with the microarray results. However, another four circRNAs were inconsistent with the microarray results, and the remaining circRNAs presented no difference between LSCC group and control group (Figure 2B).

Based on the results of the training set, the remaining 100 paired samples were enrolled in the verification set. We then studied the expression of the circRNAs validation set of the three candidates. As shown in Figure 3, we found that circ_0019201, circ_0011773 and circ_0122790 had higher expression levels confirmed by LSCC. Furthermore, the expression of the three circRNAs presented a remarkable decreasing level after surgical excision.

Risk score analysis

To further explore the accuracy and specificity of these three circRNAs as potential features, we used a risk scoring formula to evaluate the diagnostic value of these three circRNAs. Firstly, we divided the control and case groups in the training set according to the 95% confidence interval (95% CI) for the control group. Logistic regression analysis was used to calculate the risk score. All plasma samples were then divided into a high-risk group (possibly LSCC) and a low-risk group (expected to be a control group). We defined the threshold as the maximum of sensitivity plus specificity. The positive predictive value (PPV) and negative predictive value (NPV) calculated in the training set were 90% and 85%, respectively. We further applied the same values to calculate risk scores for the validation set sample, with PPV and NPV of 90% and 89%, respectively (Table 2). In addition, we also used ROC curve analysis to evaluate the predictive diagnostic value of circRNAs for LSCC. The areas under the ROC curve of the three circRNAs were 0.933, 0.908 and 0.965, respectively, which could well distinguish the areas under the ROC curve between the LSCC patients and the control group. In the validation set of amplified samples, the areas under the ROC curve of the three circRNAs were 0.766, 0.864 and 0.908, respectively. Combined with these three circRNAs, the area under the ROC curve between LSCC patients and the control group was 0.951 (Figure 4).

Stability detection of circRNAs in plasma samples

Next, we amplified these three circRNAs in five healthy controls. Human plasma obtained from three healthy controls was frozen and thawed for 5 cycles at room temperature for 0, 12, and 24 h. It was stored at –80°C for approximately seven days and digested with RNase. We found that the expression levels of these three circRNAs did not change, indicating that circ_0019201, circ_0011773, and circ_0122790 were stably expressed and detectable in human plasma (Figure 5).

Study design

A retrospective case-control study was conducted at the First People's Hospital of Lianyungang. A total of 120 patients with LSCC who were diagnosed with LSCC in department of Otolaryngology Head and Neck Surgery of the First People's Hospital of Lianyungang was enrolled from January 1, 2015, to July 1, 2019. This study was approved by an institutional review board of The First People's Hospital of Lianyungang. Written informed consents were obtained from all enrolled subjects. Blood samples from all patients were taken preoperatively or before chemoradiotherapy. Peripheral blood samples were obtained and stored in EDTA anticoagulant tubes. The blood samples were first pretreated by centrifugation at 3000rpm for 10 min. Then the plasma and precipitated samples were separated and stored in a –80°C refrigerator. All patients signed informed consent before receiving specimens. All patients with LSCC were identified by postoperative histopathological diagnosis. The American Joint Committee on Cancer (AJCC) 10th Edition Tumor-Lymph Node Metastasis (TNM) system was used for staging diagnosis in combination with preoperative imaging examination. All studies were conducted in accordance with the Helsinki Declaration.

circRNA microarray and analysis

RNA was extracted from three plasma samples diagnosed with LSCC and three healthy controls as circulating samples, both of which were used for microarray detection. Each sample was tested with a 1.0 μg total RNA. The microarray was detected by using Human CircRNA Microarray V2 (CapitalBio, Beijing, China). We screened out all the low-expression genes before performing other analyses. We only retained genes with at least half markers in five out of samples. This reduces the initial 37,681 input genes in each sample to about 15,000 detected genes. In the following analysis, we used this set of expression filter genes. We performed a bilateral Mann-Whitney U test performed by Wilcox. Finally, we use the Benjamin-Hochberg correction (R. P. Adjust function) to explain the multiple tests. For the purpose of analysis, we found that the genes significantly differentially expressed were those with a Benjamin-Hochberg Q value <0.05. We also used the Limma package to perform parallel differential expression analysis. All further data analysis and visualization is performed using custom R scripts.

RNA extraction and quantitative real-time PCR (qRT-PCR)

RNA was extracted from plasma samples using the Trizol method. The extracted RNA was qualitatively and quantitatively tested to ensure that it met subsequent validation. RNA integrity was assessed by standard denatured 1% agarose gel electrophoresis. In this study, nematode miRNA (cell-miR-39, Applied Biosystems, Foster City, CA, USA) was added to each sample as an external reference. The cDNA was synthesized by Superscript First-Strand Synthesis System (Invitrogen, Carlsbad, CA, USA). The PCR was conducted by using ABI 7900HT (Applied Biosystems, Foster City, CA, USA). The relative expression of circRNA was normalized to GAPDH and cell-miR-39 and calculated using 2^-ΔΔCQ method.

Screening phase

The screening stage is mainly divided into two stages: test combination validation group. During the trial, 20 samples from each group of patients with LSCC were randomly included for data analysis along with 20 matched healthy controls. A total of 100 samples were randomly included in the validation group for analysis.

We used a risk scoring system to predict the predictive power of single circRNAs and multiple circRNAs as the most diagnostic markers. In the cases of high expression index, we preferred to the control group on the index's 95% reference range (95% CI) as a cut-off point, if a sample of the index's expression level is higher than the cut-off point, that is defined as 1, suggest it may be closer to case group, defined as 0, conversely said tend to be more with the control group. Logistic regression analysis was conducted with the real attributes of the samples to obtain the regression coefficient. The risk score was defined based on a linear combination of the expression levels of each circRNA. The regression coefficient calculated by the risk score of multiple circRNAs for the weight of use was derived from univariate logistic regression analysis for each circRNAs. The samples were sorted according to RSF and then divided into high risk groups (representing the LSCC group) and low risk groups (representing the predictive control individuals).

Statistical analysis

If there is no special annotation, the results in this study were presented by Mean ± SEM. For continuous variables, we used ANOVA for analysis. Chi-square test was used for statistical analysis of the classification variables. All statistical analyses were performed using Stata10, and all charts were produced using GraphPad Prism.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate

Ethical approval was obtained from the Ethics Committee of the First People's Hospital of Lianyungang. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee. Informed consent was obtained from all individual participants included in the study.