Abstract
Circular RNAs (circRNAs) play important roles in the occurrence and development of cancer, and have been shown with diagnostic values in various cancers. The latest research showed that hsa_circ_0124554 is closely related to liver metastasis and vascular invasion in colorectal cancer (CRC). This study aimed to investigate whether hsa_circ_0124554 can be used as a diagnostic marker for CRC. In this study, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was used to detect hsa_circ_0124554 expression levels in 40 pairs of CRC tissues and adjacent non-tumor intestinal tissues derived from CRC patients and 32 paired plasma specimens. The relationship between the expression of hsa_circ_0124554 and the clinicopathological features of CRC patients was analyzed by t-test and chi-square test. Receiver operating characteristic (ROC) curve analysis was established to explore the diagnostic value of hsa_circ_0124554 in CRC. The results showed that hsa_circ_0124554 was substantially expressed in CRC tissues (P < .001) and that there were variations in pathological differentiation, perineural invasion and invasion. The expression of hsa_circ_0124554 in CRC patients was considerably higher than healthy controls (P < .001). The area under the receiver operating characteristic (ROC) curve (AUC) of tissue and plasma hsa_circ_0124554 was 0.703 and 0.742. The AUC of the expression combined hsa_circ_0124554, carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) had the best diagnostic performance (AUC = 0.899) in the CRC groups, and the sensitivity and specificity were 0.844 and 0.844. The expression of hsa_circ_0124554 was up-regulated in the tissues and plasma in CRC patients, which may be a new biomarker for the diagnosis of CRC. The combination hsa_circ_0124554, CEA and CA199 has the best diagnostic efficacy in CRC.
Keywords: biomarker, circRNA, colorectal cancer, diagnosis, hsa_circ_0124554
1. Introduction
Colorectal cancer (CRC) is the third most common cancer in the world, and the incidence rate of CRC continues to rise.[1] About 15% to 20% of patients have synchronous liver metastasis at the time of the first diagnosis,[2] and the 5-year survival rate of CRC patients with distant metastasis is only 60%.[3] The discovery of new biomarkers is crucial for the early detection and diagnosis of CRC as well as the development of novel treatment targets.
Circular RNAs (circRNAs), classified as endogenous non-coding RNA, are characterized by their covalent closed loop structure without 5’ cap and 3’ ends, which make them more varied, stable and conservative.[4] CircRNAs have become a research hotspot in recent years. CircRNA exerts diverse functions, including sponging microRNA, controlling transcription, and interacting with proteins,[5–7] and plays a role in tumor proliferation, invasion and migration. The presence of circRNAs was observed in CRC cells and plasma exosomes of CRC patients. Zheng et al[8] found that circLPAR1 expression in plasma exosomes of CRC patients was down-regulated, but recovered after surgery. The area under the receiver operating characteristic (ROC) curve (AUC) of exosome circLPAR1 in the diagnosis of CRC was 0.875, higher than that of carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9), suggesting that plasma exosome circLPAR1 could be used as a predictor of CRC. In the study of Yang et al,[9] circ133 was rich in plasma exosomes of CRC patients, and the expression level was increased with disease progression under the stimulation of hypoxia. Hypoxic cellular exosome circ133 promotes tumor cell metastasis through miR-133a/GEF-H1/RhoA signaling pathway and is expected to be a marker for monitoring CRC progression. Therefore, differentially expressed circRNAs can be used as biomarkers for CRC diagnosis.
Has_circ_0124554 was discovered at chr3:71090478-71096246 of the forkhead box protein 1 genome (UCSC data in NCBI). The expression of hsa_circ_0124554 is highly elevated in CRC tissues of individuals with liver metastases, and it has been linked to vascular invasion and liver metastasis in CRC.[10] CRC cells had improved migration ability when hsa_circ_0124554 was overexpressed, however, hsa_circ_0124554 knockout showed with the reverse effect. Moreover, hsa_circ_0124554 encouraged tumor metastasis by preventing the ubiquitination degradation of AKT, which stimulated the downstream PI3/AKT pathway constantly. Therefore, hsa_circ_0124554 has the potential for CRC diagnosis. In this study, we detected the expression of hsa_circ_0124554 in CRC patients and healthy individuals to assess its diagnostic value for CRC.
2. Materials and Methods
2.1. Patient specimens
This study was approved by the Ethics Review Committee of the first affiliated hospital of Ningbo university in China (NO.2023106A). The study was performed in accordance with the World Medical Association Declaration of Helsinki and all participants signed a written informed consent form. 40 tissue and matched adjacent non-tumor intestinal tissue were collected during the surgery of CRC patients. The adjacent tissues from the patient were removed from the proximal resection margin of the tumor at a distance of 10 cm. And plasma specimens were collected from 32 CRC patients and 32 healthy controls. The samples were gathered between June 2020 and April 2022. All participants signed the informed consent form. Patients’ inclusion criteria were as follows: confirmed cases; patients are willing to participate. Exclusion criteria for patients include: complex patients with additional clinical diseases; unclear pathological diagnosis; recurrent cases. Patients’ characteristics were shown in Table 1.
Table 1.
Colorectal cancer patients and healthy controls clinicopathological characteristics.
| Characteristics | Tissue | Plasma | |
|---|---|---|---|
| CRC patients (%) | CRC patients (%) | Healthy controls (%) | |
| All cases | 40 | 32 | 32 |
| Age (yr) | |||
| <60 | 9 (22.5) | 11 (34.4) | 19 (59.4) |
| ≥60 | 31 (77.5) | 21 (65.6) | 13 (40.6) |
| Gender | |||
| Male | 25 (62.5) | 19 (59.4) | 15 (46.9) |
| Female | 15 (37.5) | 13 (40.6) | 17 (53.1) |
| Diameter (cm) | |||
| ≥5 | 17 (42.5) | ||
| <5 | 23 (57.5) | ||
| Differentiation | |||
| Well and moderate | 29 (72.5) | ||
| Poor | 11 (27.5) | ||
| Lymphatic metastasis | |||
| Positive | 19 (47.5) | ||
| Negative | 21 (52.5) | ||
| Lymphovascular invasion | |||
| Present | 18 (45.0) | ||
| Absent | 22 (55.0) | ||
| Perineural invasion | |||
| Present | 13 (32.5) | ||
| Absent | 27 (67.5) | ||
| Distant metastasis | |||
| M0 | 38 (95.0) | ||
| M1 | 2 (5.0) | ||
| Invasion | |||
| Tis-T2 | 8 (20.0) | ||
| T3-T4 | 32 (80.0) | ||
| TNM stage | |||
| 0-II | 22 (55.0) | ||
| III-IV | 18 (45.0) | ||
| Primary tumor site | |||
| Colon | 24 (60.0) | ||
| Rectum | 16 (40.0) | ||
| CEA in μg/L | |||
| ≥5 | 18 (45.0) | 10 (31.3) | 0 (0.0) |
| <5 | 22 (55.0) | 22 (68.8) | 32 (100.0) |
| CA19-9 in U/mL | |||
| ≥25 | 10 (25.0) | 9 (28.1) | 1 (3.1) |
| <25 | 30 (75.0) | 23 (71.9) | 31 (96.9) |
CA19-9 = carbohydrate antigen 19-9, CEA = carcinoembryonic antigen, TNM = tumor node metastasis.
The diagnosis of CRC was confirmed by Ningbo Diagnostic Pathology Center, China. The tumor stage was determined according to the CRC tumor-node-metastasis staging system of American Joint Commission on Cancer (AJCC)/union for international cancer control (UICC).
The 40 CRC tissues and their adjacent-normal tissue were obtained and put into RNA-fixer Reagent and stored at −80ºC. All the tumors in the study were adenocarcinoma. The peripheral blood of 32 participants was collected in ethylenediaminetetraacetic acid (EDTA) anticoagulant tubes and centrifuged for 3000 × g for 10 minutes at room temperature, and the upper plasma was obtained and stored at −80ºC.
2.2. RNA extraction and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR)
Total RNA was isolated from CRC tumor tissue, adjacent normal intestinal tissue and plasma samples by using TRIzol reagent and TRIzol LS reagent (Invitrogen, Carlsbad, California, United States). The extracted RNA was then converted into cDNA using the GoScript Reverse Transcription System (Promega Corporation, Madison, WI, USA). The qRT-PCR was performed using GoTaq qPCR Master Mix (Promega Corporation, Madison, WI, USA) by applying a MX3005P qPCR System (Stratagene, La Jolla, CA, USA) to quantify the expression levels of hsa_circ_0124554, with GAPDH serving as the internal control. The qRT-PCR results were expressed as ΔCt value with calculation formula ΔCt = ΔCt (circRNA) - ΔCt(GADPH). All values were presented as mean ± standard deviation. The lower the ΔCt value, the higher the expression level of hsa_circ_0124554. All qRT-PCR analyses were performed in 3 biological repeats.
Primer sequences were as follows: Hsa_circ_0124554 forward, 5’-TGACCACGACATGTGTCTCC-3’, and reverse, 5’-TGCTGCATCTGTAAAACTTTCCC-3’; GAPDH forward, 5’-GAGCTGAACGGGAAGCTCACTG-3’, and reverse, 5’-TGGTGCTCAGTGTAGCCCAGGA-3’. The thermal conditions of PCR are as follows: 95ºC for 5 minutes, then 40 cycles at 95ºC for 30 seconds and 60ºC for 50 seconds, 72ºC for 30 seconds finally.
2.3. Statistical analysis
All experimental data were obtained using SPSS software (version 22.0; IBM, Armonk, NY, United States) and GraphPad Prism 9.4.1 (GraphPad Software, LLC, United States). Student t test was used to evaluate the significance of differences between CRC tissue and adjacent non-tumor intestinal tissue, as well as between plasma samples from CRC patients and healthy controls. The tissue expression levels were analyzed by 2-delta delta Ct (2-ΔΔCt) method. The CRC patients were divided into the high and low expression groups according to the median hsa_circ_0124554 expression level. The chi-square test was used to analyze the expression level of the hsa_circ_0124554 in the patients with different clinicopathological factors. In addition, logistic regression and the receiver operating characteristic (ROC) curve were established to evaluate AUC, sensitivity and specificity in the diagnosis of hsa_circ_0124554, CEA, CA19-9 and combined CEA and CA19-9. P < .05 was considered statistically significant.
3. Results
3.1. Increased expression of hsa_circ_0124554 in tissues in CRC patients
The expression level of hsa_circ_0124554 was detected by qRT-PCR and results were reported. Relatively expression levels of hsa_circ_0124554 in the CRC tissues and adjacent non-tumor intestinal tissue were 11.96 ± 0.50 and 12.46 ± 0.70. As shown in Figure 1, in 29 pairs (72.50%) of samples, hsa_circ_0124554 expression in CRC tissues was significantly higher than that in non-tumor tissues. The findings demonstrated that hsa_circ_0124554 was up-regulated in CRC tissues compared with normal tissues (P < .001).
Figure 1.
The expression of hsa_circ_0124554 was detected in CRC tissues and adjacent non-tumor intestinal tissues. ***P < .001, n = 40. The lower the ΔCt value means the higher expression.
3.2. Increased expression of hsa_circ_0124554 in plasma in CRC patients
The plasma samples were analyzed by qRT-PCR. In the CRC group and healthy control group, the relative expression levels of hsa_circ_0124554 were 15.26 ± 0.62 and 16.29 ± 1.48, respectively. The results showed that the expression level of hsa_circ_0124554 was significantly increased in the CRC group compared with the healthy control group (Fig. 2) (P < .001).
Figure 2.
The expression levels of hsa_circ_0124554 in plasma of CRC patients and healthy controls. ***P < .001, n = 32. The lower the ΔCt value means the higher expression.
3.3. Association of hsa_circ_0124554 expression levels in tissues and plasma with clinicopathological features of patients
Then the study measured the median expression level of hsa_circ_0124554 in CRC tissue. According to the median for hsa_circ_0124554 expression level, CRC patients were divided into the high and low expression groups. Associations between the expression of hsa_circ_0124554 and patients’ clinicopathological features were analyzed with chi-square test. According to the results (Table 2), the hsa_circ_0124554 level in CRC tissue was significantly related to pathological differentiation (P = .001), perineural invasion (PNI)(P = .018), and invasion (P = .044), but not with other clinical traits including age, gender, tumor diameter, lymphovascular invasion, tumor-node-metastasis stage, primary tumor site, CEA, or CA19-9.
Table 2.
The relationship between hsa_circ_0124554 expression (2-ΔΔCt) and clinicopathological features in colorectal cancer patients.
| Clinicopathological factor | No of cases | Hsa_circ_0124554 expression level | P value | |
|---|---|---|---|---|
| High(%) | Low(%) | |||
| All cases | 40 | 20 (50.0) | 20 (50.0) | |
| Age (yr) | >.999 | |||
| <60 | 9 | 4 (44.4) | 5 (55.6) | |
| ≥60 | 31 | 16 (51.6) | 15 (48.4) | |
| Gender | .744 | |||
| Male | 25 | 13 (52.0) | 12 (48.0) | |
| Female | 15 | 7 (46.7) | 8 (53.3) | |
| Diameter(cm) | .337 | |||
| ≥5 | 17 | 7 (41.2) | 10 (58.8) | |
| <5 | 23 | 13 (56.5) | 10 (43.5) | |
| Differentiation | .001 | |||
| Well and moderate | 29 | 10 (34.5) | 19 (65.5) | |
| Poor | 11 | 10 (90.9) | 1 (9.1) | |
| Lymphatic metastasis | .752 | |||
| Positive | 19 | 10 (52.6) | 9 (47.4) | |
| Negative | 21 | 10 (47.6) | 11 (52.4) | |
| Lymphovascular invasion | .057 | |||
| Present | 18 | 12 (66.7) | 6 (33.3) | |
| Absent | 22 | 8 (36.4) | 14 (63.6) | |
| Perineural invasion | .018 | |||
| Present | 13 | 10 (76.9) | 3 (23.1) | |
| Absent | 27 | 10 (37.0) | 17 (63.0) | |
| Distant metastasis | .487 | |||
| M0 | 38 | 18 (47.4) | 20 (52.6) | |
| M1 | 2 | 2 (100.0) | 0 (0) | |
| Invasion | .044 | |||
| Tis-T2 | 8 | 1 (12.5) | 7 (87.5) | |
| T3-T4 | 32 | 19 (59.4) | 13 (40.6) | |
| TNM stage | .525 | |||
| 0-II | 22 | 10 (45.5) | 12 (54.5) | |
| III-IV | 18 | 10 (55.6) | 8 (44.4) | |
| Primary tumor site | .519 | |||
| Colon | 24 | 11 (45.8) | 13 (54.2) | |
| Rectum | 16 | 9 (56.3) | 7 (43.8) | |
| CEA in μg/L | >.999 | |||
| ≥5 | 18 | 9 (50.0) | 9 (50.0) | |
| <5 | 22 | 11 (50.0) | 11 (50.0) | |
| CA19-9 in U/mL | >.999 | |||
| ≥25 | 10 | 5 (50.0) | 5 (50.0) | |
| <25 | 30 | 15 (50.0) | 15 (50.0) | |
The bold symbol means statistical significance.
CA19-9 = carbohydrate antigen 19-9, CEA = carcinoembryonic antigen, TNM = tumor node metastasis.
3.4. ROC curve analysis of hsa_circ_0124554
A ROC curve was established to evaluate the potential diagnostic value of hsa_circ_0124554 in CRC. The result displayed that the AUC for hsa_circ_0124554 in tissue was 0.703 (95% CI: 0.590–0.815, P < .005) (Fig. 3A), while the cutoff value, sensitivity and specificity were 12.830, 0.975 and 0.350, respectively. As shown in Figure 3B, the AUC of hsa_circ_0124554 in plasma was 0.742 (95% CI: 0.620–0.864, P < .001), and the cutoff value, sensitivity, and specificity were 16.013, 0.938, and 0.469. Then, ROC curve analysis was used to compare the diagnostic power between hsa_circ_0124554 and the traditional tumor markers CEA and CA19-9 (Fig. 3C). The AUC area of CEA was 0.831, and that of CA19-9 was 0.646. In this study, we explored different combinations of 2 or 3 of the markers hsa_circ_0124554, CEA and CA199. The diagnostic efficacy of different combinations was as follows. As shown in Figure 3D, the AUC area of hsa_circ_0124554 + CEA was 0.886 (95% CI: 0.808–0.963, P < .001), and the sensitivity and specificity were 0.812 and 0.812. The AUC of hsa_circ_0124554 + CA19-9 was 0.817 (95% CI: 0.716–0.919, P < .001), while the sensitivity and specificity were 0.844 and 0.719. The AUC value after the combination of all 3 was 0.899 (95% CI: 0.827–0.972, P < .001), which were higher than those of any biomarkers alone or in combination, and their combined diagnostic sensitivity and specificity were also as high as 0.844.
Figure 3.
The role of hsa_circ_0124554 in diagnosing CRC. (A) ROC curve of hsa_circ_0124554 expression in tissue; The AUC of hsa_circ_0124554 was up to 0.703. (B) ROC curve analysis of hsa_circ_0124554 expression in plasma; The AUC was 0.742. (C) Comparison of diagnostic value curves of plasma hsa_circ_0124554 with CEA and CA19-9. (D) ROC curve analysis of combined diagnosis of hsa_circ_0124554 in plasma. AUC = the area under the ROC curve, CEA = carcinoembryonic antigen, CA19-9 = carbohydrate antigen 19-9.
4. Discussion
One of the prevalent gastrointestinal malignancies, CRC is influenced by several variables, including intestinal flora, gene mutation, and tumor microenvironment.[11–13] The pathophysiology and treatment of CRC have evolved recently, but the prognosis for patients with advanced CRC remains dismal, and the 5-year survival rate of stage IV CRC patients is just 12%.[14] There is an urgent need for noninvasive biomarkers to facilitate early diagnosis and therapy of CRC. The properties of circRNA have been thoroughly investigated and are thought to be workable diagnostic techniques and biomarkers.[15] CircRNA was first discovered in 1976 and initially believed to be the result of incorrect splicing,[16] but as high-throughput sequencing technology have advanced, circRNA has been more thoroughly investigated and evaluated. CircRNA has been demonstrated to play a role in the development, expansion, migration, and invasion of CRC. CircRNA 0000392 was up-regulated in CRC tissues, where it facilitated the development of the phosphoinositide-3-Kinase Regulatory Subunit 3/AKT pathway by sponging miR-193a-5p, hence promoting tumor growth and invasion.[17] CircMTO1 can be exploited as a potential biomarker because its low expression accelerated the malignant development of CRC cells by triggering the Wnt/β-catenin pathway.[18] These findings suggest that circRNA can be served as a promising tumor biomarker and provide information for novel diagnostic and therapeutic strategies.
Hsa_circ_0124554, which has been demonstrated to be closely related to liver metastasis of CRC, was measured in this study.[10] We detected the expression of 40 pairs of CRC tissues and adjacent-normal tissues. Hsa_circ_0124554 was elevated in CRC tissues (Fig. 1), which was consistent with the preliminary investigation findings. The highly conserved sequence of circRNA, which has a circular shape and can withstand exonuclease RNase R interference, makes it more stable than linear RNA.[19] CircRNA can be remain stable in bodily fluids like urine, blood, saliva, and particularly plasma due to the structural specificity of the molecule.[20] We further verified the expression of hsa_circ_0124554 in plasma using qRT-PCR analysis. The results showed that the expression of hsa_circ_0124554 was higher in the plasma samples of CRC patients when compared with that in the healthy control group (Fig. 2).
Several clinicopathological factors such as tumor differentiation, PNI and invasion are important in the prognostication of CRC patients.[21] By employing a retrospective cohort study, Fang et al[22] suggested that CRC patients with poorer differentiation status suffer poorer outcomes and assume a higher risk of recurrence. Moreover, PNI refers to a method of tumor spread and occurs more frequently in a higher stage of CRC. Leijssen et al[23] reported that positive PNI is associated with worse disease-free survival, worse overall survival and worse disease-specific survival. Tumor invasion has been shown to influence survival. Tsikitis et al[24] demonstrated patients with T4 tumors were 3 times more likely to recur than patients with T3 tumors. In our study, the expression level in the tissue of hsa_circ_0124554 was related to the clinicopathological factors of CRC patients such as differentiation, PNI and invasion (Table 2). These clinicopathological factors are independent prognostic features in CRC. The results mean that hsa_circ_0124554 is an indicator of the prognosis of patients with CRC.
We used hsa_circ_0124554 to performed the ROC curve analysis to confirm the efficacy of CRC screening and diagnosis. The ROC curve is a comprehensive index that is frequently used to reflect the sensitivity and specificity of chosen indicators. In general, the test with higher AUC areas was considered with great diagnostic value. The findings demonstrated that hsa_circ_0124554 could be used to distinguish between healthy individuals and CRC patients (Fig. 3A and B). The AUC and cutoff value of the tissue ROC curve were 0.703 and 12.830, respectively, while those of the plasma hsa_circ_0124554 were 0.742 and 16.013, both of which had some degree of diagnostic accuracy. According to the findings in Figure 3C, hsa_circ_0124554 may be more useful than CA19-9 in the diagnosis of patients with suspected CRC. Studies have reported that the AUC of CEA in the diagnosis of CRC ranged from 0.709 to 0.739,[25–27] but our data showed that the AUC of CEA was 0.831, which may be related to the insufficient sample size in our study. In addition to evaluating the performance of each single marker in detection, we also combined 2 or 3 tumor markers to find the optimal diagnostic combination. The results showed that the sensitivity of any combination was higher than that of a single marker. The ROC curve results of hsa_circ_0124554 combined with CEA and CA19-9 showed the largest AUC area (AUC = 0.899) and the highest accuracy, exhibiting superior diagnostic signs of advantage (Fig. 3D), confirming the accuracy and clinical feasibility of this circRNA as a screening and diagnosis for CRC.
The present study has some limitations. The evaluation of the association between hsa_circ_0124554 and CRC pathological factors was impacted by the study limited sample size of patients, which may lead to bias in the findings and lower the study representation. Additional studies with sufficient sample numbers should be conducted in order to further confirm that hsa_circ_0124554 may be used as a CRC diagnostic marker for clinical application in the future.
5. Conclusion
The findings of this study demonstrated that hsa_circ_0124554 expression was markedly up-regulated in CRC tissue. Compared to the healthy control group, plasma samples from CRC patients had higher levels of hsa_circ_0124554 expression, which when combined with CEA could improve diagnostic accuracy. Hsa_circ_0124554 was also related to the clinicopathologic characteristics of CRC patients. Finally, hsa_circ_0124554 might be a brand-new CRC biomarker.
Author contributions
Conceptualization: Tong Li, Yanping Qing.
Data curation: Kexin Li.
Formal analysis: Kexin Li, Tong Li, Zhuocheng Yu, Qingqing Yuan.
Funding acquisition: Yanping Qing.
Investigation: Kexin Li, Zhuocheng Yu, Qingqing Yuan.
Methodology: Kexin Li, Tong Li.
Project administration: Tong Li, Yanping Qing.
Resources: Kexin Li, Tong Li, Yanping Qing.
Software: Kexin Li.
Supervision: Tong Li, Yanping Qing.
Validation: Kexin Li.
Visualization: Kexin Li, Zhuocheng Yu, Qingqing Yuan.
Writing – original draft: Kexin Li.
Writing – review & editing: Kexin Li, Yanping Qing.
Abbreviations:
- AUC
- area under curve
- CA19-9
- carbohydrate antigen 19-9
- CEA
- carcinoembryonic antigen
- circRNAs
- circular RNAs
- CRC
- colorectal cancer
- GEF-H1
- guanine nucleotide exchange factor-H1
- PNI
- perineural invasion
- qRT-PCR
- quantitative reverse transcriptase polymerase chain reaction
- ROC
- receiver operating characteristic
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
This Project is Supported by Ningbo Natural Science Foundation (202003N4202). The authors declare that they have no competing interests.
The authors have no conflicts of interest to disclose.
How to cite this article: Li K, Li T, Yu Z, Yuan Q, Qing Y. Hsa_circ_0124554 may serve as a biomarker for the diagnosis of colorectal cancer: An observational study. Medicine 2023;102:48(e36353).
Contributor Information
Kexin Li, Email: leetongmail989@163.com.
Tong Li, Email: leetongmail989@163.com.
Zhuocheng Yu, Email: jhmsyuzhuocheng@163.com.
Qingqing Yuan, Email: 1468258838@qq.com.
References
- [1].Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71:209–49. [DOI] [PubMed] [Google Scholar]
- [2].Manfredi S, Lepage C, Hatem C, et al. Epidemiology and management of liver metastases from colorectal cancer. Ann Surg. 2006;244:254–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [3].La Vecchia S, Sebastián C. Metabolic pathways regulating colorectal cancer initiation and progression. Semin Cell Dev Biol. 2020;98:63–70. [DOI] [PubMed] [Google Scholar]
- [4].Xiao MS, Ai Y, Wilusz JE. Biogenesis and functions of circular RNAs come into focus. Trends Cell Biol. 2020;30:226–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Liu J, Chen S, Li Z, et al. Hsa_circ_0040809 and hsa_circ_0000467 promote colorectal cancer cells progression and construction of a circRNA-miRNA-mRNA network. Front Genet. 2022;13:993727. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Abdelmohsen K, Panda AC, Munk R, et al. Identification of HuR target circular RNAs uncovers suppression of PABPN1 translation by CircPABPN1. RNA Biol. 2017;14:361–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Li Z, Huang C, Bao C, et al. Exon-intron circular RNAs regulate transcription in the nucleus. Nat Struct Mol Biol. 2015;22:256–64. [DOI] [PubMed] [Google Scholar]
- [8].Zheng R, Zhang K, Tan S, et al. Exosomal circLPAR1 functions in colorectal cancer diagnosis and tumorigenesis through suppressing BRD4 via METTL3-eIF3h interaction. Mol Cancer. 2022;21:49. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9].Yang H, Zhang H, Yang Y, et al. Hypoxia induced exosomal circRNA promotes metastasis of Colorectal Cancer via targeting GEF-H1/RhoA axis. Theranostics. 2020;10:8211–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [10].Tang J, Zhang C, Huang Y, et al. CircRNA circ_0124554 blocked the ubiquitination of AKT promoting the skip lymphovascular invasion on hepatic metastasis in colorectal cancer. Cell Death Dis. 2021;12:270. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [11].Zhu G, Pei L, Xia H, et al. Role of oncogenic KRAS in the prognosis, diagnosis and treatment of colorectal cancer. Mol Cancer. 2021;20:143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [12].Chen S, Zhang L, Li M, et al. Fusobacterium nucleatum reduces METTL3-mediated m(6)A modification and contributes to colorectal cancer metastasis. Nat Commun. 2022;13:1248. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Wei C, Yang C, Wang S, et al. Crosstalk between cancer cells and tumor associated macrophages is required for mesenchymal circulating tumor cell-mediated colorectal cancer metastasis. Mol Cancer. 2019;18:64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [14].Miller KD, Nogueira L, Mariotto AB, et al. Cancer treatment and survivorship statistics, 2019. CA Cancer J Clin. 2019;69:363–85. [DOI] [PubMed] [Google Scholar]
- [15].Chen L, Wang C, Sun H, et al. The bioinformatics toolbox for circRNA discovery and analysis. Brief Bioinform. 2021;22:1706–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Sanger HL, Klotz G, Riesner D, et al. Viroids are single-stranded covalently closed circular RNA molecules existing as highly base-paired rod-like structures. Proc Natl Acad Sci U S A. 1976;73:3852–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [17].Xu H, Liu Y, Cheng P, et al. CircRNA_0000392 promotes colorectal cancer progression through the miR-193a-5p/PIK3R3/AKT axis. J Exp Clin Cancer Res. 2020;39:283. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [18].Ge Z, Li LF, Wang CY, et al. CircMTO1 inhibits cell proliferation and invasion by regulating Wnt/β-catenin signaling pathway in colorectal cancer. Eur Rev Med Pharmacol Sci. 2018;22:8203–9. [DOI] [PubMed] [Google Scholar]
- [19].Li A, Wang WC, McAlister V, et al. Circular RNA in colorectal cancer. J Cell Mol Med. 2021;25:3667–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [20].Zhou Q, Ju LL, Ji X, et al. Plasma circRNAs as Biomarkers in Cancer. Cancer Manag Res. 2021;13:7325–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [21].Chen K, Collins G, Wang H, et al. Pathological Features and Prognostication in Colorectal Cancer. Curr Oncol. 2021;28:5356–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [22].Fang L, Yang Z, Zhang M, et al. Clinical characteristics and survival analysis of colorectal cancer in China: a retrospective cohort study with 13,328 patients from southern China. Gastroenterol Rep (Oxf). 2021;9:571–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Leijssen LGJ, Dinaux AM, Taylor MS, et al. Perineural invasion is a prognostic but not a predictive factor in nonmetastatic colon cancer. Dis Colon Rectum. 2019;62:1212–21. [DOI] [PubMed] [Google Scholar]
- [24].Tsikitis VL, Larson DW, Huebner M, et al. Predictors of recurrence free survival for patients with stage II and III colon cancer. BMC Cancer. 2014;14:336. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [25].Cao H, Zhu L, Li L, et al. Serum CA724 has no diagnostic value for gastrointestinal tumors. Clin Exp Med. 2023;23:2433–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [26].Li P, Chen J, Chen Y, et al. Construction of Exosome SORL1 detection platform based on 3D porous microfluidic chip and its application in early diagnosis of colorectal cancer. Small. 2023;19:e2207381. [DOI] [PubMed] [Google Scholar]
- [27].Li H, Wang X, Huang X, et al. Circulating glycan monosaccharide composite-based biomarker diagnoses colorectal cancer at early stages and predicts prognosis. Front Oncol. 2022;12:852044. [DOI] [PMC free article] [PubMed] [Google Scholar]