Literature DB >> 34216509

Circular RNA_0001946 is insufficiently expressed in tumor tissues, while its higher expression correlates with less lymph node metastasis, lower TNM stage, and improved prognosis in NSCLC patients.

Minghua Zhang1, Fangjing Wen1, Ke Zhao2.   

Abstract

OBJECTIVE: Circular RNA_0001946 (circ_0001946) inhibits tumor progression but promotes chemosensitivity in non-small-cell lung cancer (NSCLC); however, its correlation with tumor features and prognosis in NSCLC patients is still unclear; therefore, this study aimed to investigate these issues.
METHODS: A total of 284 NSCLC patients were retrospectively analyzed. Circ_0001946 expression in tumor (n = 284) and adjacent (n = 125) tissues was detected by the reverse transcription-quantitative polymerase chain reaction. Meanwhile, patients' clinical characteristics, recurrence, and survival data were extracted from the electrical database.
RESULTS: Circ_0001946 expression in adjacent tissues was over 3-folds as that in tumor tissues (P < .001). Meanwhile, higher tumor circ_0001946 expression was correlated with less lymph node metastasis (P < .001) and decreased TNM stage (P = .001), but did not correlate with other clinicopathological features. Moreover, higher tumor circ_0001946 expression was associated with prolonged disease-free survival (DFS) (P < .001) and overall survival (OS) (P < .001), respectively. Subgroup analyses revealed that higher tumor circ_0001946 was correlated with improved DFS in patients with TNM stage I, II, or III, respectively (all P < .05), while only correlated with prolonged OS in patients with TNM stage III (P = .037), but not in patients with TNM stage I or II. Further multivariate Cox's proportional hazard regression analyses suggested that higher tumor circ_0001946 expression could independently predict improved DFS (P < .001, hazard ratio (HR) = 0.719) and OS (P < .001, HR = 0.746), respectively.
CONCLUSION: Circ_0001946 is insufficiently expressed in tumor tissues, whereas its higher expression correlates with less lymph node metastasis, reduced TNM stage, and improved prognosis in NSCLC patients.
© 2021 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC.

Entities:  

Keywords:  circular RNA_0001946; disease-free survival; non-small-cell lung cancer; overall survival; tumor features

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Year:  2021        PMID: 34216509      PMCID: PMC8373335          DOI: 10.1002/jcla.23625

Source DB:  PubMed          Journal:  J Clin Lab Anal        ISSN: 0887-8013            Impact factor:   2.352


INTRODUCTION

Non‐small‐cell lung cancer (NSCLC) is a global health issue that affects over 2.1 million people and causes above 1.7 million deaths annually. Thanks to the improvement in early detection techniques and treatment strategies for NSCLC, the mortality of NSCLC patients has decreased slightly in western countries in recent years., , However, partly due to the increase in smoking population and air pollution in the past decades, the incidence of NSCLC is still rising in China, thus making NSCLC a major public health concern., One potential strategy to ameliorate this situation might be searching for novel prognostic biomarkers in NSCLC patients to improve the management toward them., In recent years, circular RNAs (circRNAs) have received vast interest from the researchers, and numerous studies have revealed that circRNAs could regulate the initiation and progression of various diseases, including cancer., CircRNA_0001946 (circ_0001946), as a newly discovered circRNA, has been reported to participate in the progression of several cancers. For instance, in glioblastoma, circ_0001946 suppresses proliferation, migration, and invasion both in vitro and in vivo; in bladder cancer, it also represses cell proliferation, migration, and invasion, while, in colorectal cancer, circ_0001946 promotes cell proliferation and epithelial‐mesenchymal transition. Moreover, in NSCLC, it is reported that circ_0001946 reduces cancer cell proliferation, migration, and invasion, but promotes cancer cell chemosensitivity to cisplatin. Based on the effect of circ_0001946 on tumor cell progression and chemosensitivity in cancers including NSCLC, we hypothesized that circ_0001946 might be a potential clinical biomarker in NSCLC, whereas relevant information is unclear. In this retrospective study, we enrolled 284 surgical NSCLC patients, aimed to investigate circ_0001946 relative expression and its correlation with tumor characteristics as well as prognosis in NSCLC.

MATERIALS AND METHODS

Patients

This study retrospectively reviewed 284 NSCLC patients who received resection in our hospital from January 2015 to December 2019. All patients were confirmed as NSCLC by pathological evaluation. The adult patients who had well‐preserved freshly frozen tumor tissues and complete clinical/follow‐up data were included in this study. In addition, the patients who received neoadjuvant therapy or history of/complicated with other cancers were excluded. This study was approved by the Ethics Committee of our hospital. All patients or their family members provided written informed consents.

Data collection

The clinical data were collected from patients’ electronic medical records, which included age, gender, history of smoke, history of drink, hypertension, hyperlipidemia, diabetes, differentiation, tumor size, lymph node metastasis, TNM stage, and carcinoembryonic antigen (CEA) level. The follow‐up data were collected from the follow‐up record, and the last follow‐up date was January 31, 2020. The disease status and survival status were obtained from the follow‐up data, and disease‐free survival (DFS) and overall survival (OS) were calculated. DFS was defined as the duration from surgery to the date of disease relapse or death. OS was defined as the duration from surgery to the date of death.

Circ_0001946 detection

Freshly frozen tumor tissues of 284 patients were acquired from the storeroom of the Pathology Department. Besides, 125 patients among 284 patients also had paired freshly frozen adjacent tissues, and the 125 adjacent tissues were collected as well. The expression of circ_0001946 in tumor tissues and adjacent tissues was detected by reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR) in accordance with the method described in a previous study with some modification. In brief, TRIzol™ Reagent (Thermo Fisher Scientific) was used for total RNA extraction. Next, for circRNA detection, RNase R (Epicentre) was used to digest linear RNA, while, for GAPDH RNA detection, linear RNA digestion was not conducted. Subsequently, PrimeScript™ RT reagent Kit (Takara) was applied for reverse transcription, and TB Green™ Fast qPCR Mix (Takara) was used for qPCR. All reagents or kits were used under the manufacturers’ instructions. GAPDH was used as the internal reference, and circ_0001946 relative expression was calculated by the 2−ΔΔCt formula. The primers were designed according to the previous study. Circ_0001946 forward primer: 5′‐TCCAGTGTGCTGATCTTCTGAC‐3′, reverse primer: 5′‐TGGAAGACCCGGAGTTGTTG‐3′; GAPDH forward primer: 5′‐GACCACAGTCCATGCCATCAC‐3′, reverse primer: 5′‐ACGCCTGCTTCACCACCTT‐3′.

Statistical analysis

Statistical analysis was performed with the use of SPSS 24.0 (IBM). The figures were plotted using GraphPad Prism 8.01 (GraphPad Software lnc.). The Kolmogorov‐Smirnov test was used for the normality test of continuous variables. Normally distributed continuous variables were displayed as mean ± standard deviation (SD), and unknown distributed continuous variables were expressed as median with interquartile range (IQR). Categorical variables were presented as numbers and percentages. Wilcoxon rank‐sum test was used to compare circ_0001946 expression between adjacent tissues and tumor tissues. In order to analyze the correlation of tumor circ_0001946 expression with clinical characteristics and prognosis, the expression of circ_0001946 in tumor tissue was further categorized as Q1 (quartile 1%‐25%), Q2 (quartile 25%‐50%), Q3 (quartile 50%‐75%), and Q4 (quartile 75%‐100%). Linear‐by‐linear association test or Spearman's rank correlation test was used to analyze the correlation of circ_0001946 with clinical characteristics. Kaplan‐Meier curve was plotted, and the log‐rank test was used for comparing the difference in DFS and OS among groups. Forward stepwise multivariate Cox's proportional hazard regression model was used to analyze the factors correlated with DFS and OS P value < .05 was considered as significant.

RESULTS

Description of patients’ characteristics

A total of 457 NSCLC patients who received resection were screened, and 85 of them were excluded (including 46 patients who were unable to contact and 39 patients who refused to participate). Then, the remaining 372 patients were reviewed; then, 88 of them were excluded (including 42 patients who received neoadjuvant therapy, 26 patients who had no eligible tumor tissue, and 20 patients who had no complete clinical or follow‐up data). Finally, 284 eligible NSCLC patients were analyzed (Figure 1). Patients’ characteristics were shown in Table 1. Briefly, the mean age of patients was 63.0 ± 11.3 years, 56 (19.7%) patients were female, and 228 (80.3%) patients were male. With regard to tumor differentiation, 53 (18.7%) patients were well differentiated, 166 (58.5%) patients were moderately differentiated, and 65 (22.9%) patients were poorly differentiated. Meanwhile, the mean tumor size was 5.4 ± 2.1 cm, 163 (57.4%) patients had tumor size less than or equal to 5.0 cm, and 121 (42.6%) patients had tumor size greater than 5.0 cm. Besides, 190 (66.9%) patients did not have lymph node metastasis, while 94 (33.1%) patients had lymph node metastasis. As to TNM stage, 89 (31.3%) patients were of stage I, 103 (36.3%) patients were of stage II, and 92 (32.4%) patients were of stage III. Moreover, the median level of CEA was 5.7 (2.5‐26.8) ng/mL, 134 (47.2%) patients were of normal CEA level, and 150 (52.8%) patients were of abnormal CEA level.
Figure 1

Study flow. NSCLC, non‐small‐cell lung cancer

Table 1

Patients’ characteristics

ItemsNSCLC patients (n = 284)
Age (y), mean ± SD63.0 ± 11.3
≤60 y, no. (%)110 (38.7)
>60 y, no. (%)174 (61.3)
Gender, No. (%)
Female56 (19.7)
Male228 (80.3)
History of smoke, No. (%)
No128 (45.1)
Yes156 (54.9)
History of drink, No. (%)
No169 (59.5)
Yes115 (40.5)
Hypertension, No. (%)
No183 (64.4)
Yes101 (35.6)
Hyperlipidemia, No. (%)
No192 (67.6)
Yes92 (32.4)
Diabetes, No. (%)
No241 (84.9)
Yes43 (15.1)
Tumor differentiation, No. (%)
Well53 (18.7)
Moderate166 (58.5)
Poor65 (22.9)
Tumor size (cm), mean ± SD5.4 ± 2.1
≤5.0 cm, no. (%)163 (57.4)
>5.0 cm, no. (%)121 (42.6)
Lymph node metastasis, No. (%)
No190 (66.9)
Yes94 (33.1)
TNM stage, No. (%)
I89 (31.3)
II103 (36.3)
III92 (32.4)
CEA (ng/mL), median (IQR)5.7 (2.5‐26.8)
Normal (≤5 ng/mL), no. (%)134 (47.2)
Abnormal (>5 ng/mL), no. (%)150 (52.8)
Adjuvant therapy
No adjuvant therapy61 (21.5)
CT136 (47.9)
RT60 (21.1)
CCRT71 (25.0)

Abbreviations: CCRT, concurrent chemoradiotherapy; CEA, carcinoembryonic antigen; CT, chemotherapy; IQR, interquartile range; NSCLC, non‐small‐cell lung cancer; RT, radiotherapy; SD, standard deviation.

Study flow. NSCLC, non‐small‐cell lung cancer Patients’ characteristics Abbreviations: CCRT, concurrent chemoradiotherapy; CEA, carcinoembryonic antigen; CT, chemotherapy; IQR, interquartile range; NSCLC, non‐small‐cell lung cancer; RT, radiotherapy; SD, standard deviation.

Circ_0001946 expression

RT‐qPCR analysis showed that the median level of circ_0001946 in adjacent tissues (median level: 1.000 (0.750‐1.294)) was over 3‐folds as that in tumor tissues (median level: 0.291 (0.194‐0.436) in NSCLC patients (P < .001) (Figure 2).
Figure 2

Circ_0001946 expression in tumor tissues and adjacent tissues of NSCLC patients. Circ_0001946, circular RNA_0001946; NSCLC, non‐small‐cell lung cancer

Circ_0001946 expression in tumor tissues and adjacent tissues of NSCLC patients. Circ_0001946, circular RNA_0001946; NSCLC, non‐small‐cell lung cancer

Correlation of tumor circ_0001946 expression with clinical characteristics

Subsequently, correlation analysis revealed that tumor circ_0001946 expression was negatively correlated with lymph node metastasis (P < .001) and TNM stage (P = .001). However, no correlation was observed in tumor circ_0001946 expression with age (P = .446), gender (P = .187), history of smoke (P = .670), history of drink (P = .075), hypertension (P = .293), hyperlipidemia (P = 1.000), diabetes (P = .941), tumor differentiation (P = .185), tumor size (P = .097), or CEA level (P = .089) in NSCLC patients (Table 2).
Table 2

Correlation analysis between circ_0001946 and clinical characteristics

ItemsCirc_0001946 expressiona P value
Q1 (0%‐25%, n = 71)Q2 (25%‐50%, n = 71)Q3 (50%‐75%, n = 71)Q4 (75%‐100%, n = 71)
Age, No. (%).446
≤60 y28 (39.4)30 (42.3)28 (39.4)24 (33.8)
>60 y43 (60.6)41 (57.7)43 (60.6)47 (66.2)
Gender, No. (%).187
Female10 (14.1)19 (26.8)11 (15.5)16 (22.5)
Male61 (85.9)52 (73.2)60 (84.5)55 (77.5)
History of smoke, No. (%).670
No33 (46.5)32 (45.1)33 (46.5)30 (42.3)
Yes38 (53.5)39 (54.9)38 (53.5)41 (57.7)
History of drink, No. (%).075
No39 (54.9)38 (53.5)44 (62.0)48 (67.6)
Yes32 (45.1)33 (46.5)27 (38.0)23 (32.4)
Hypertension, No. (%).293
No40 (56.3)48 (67.6)49 (69.0)46 (64.8)
Yes31 (43.7)23 (32.4)22 (31.0)25 (35.2)
Hyperlipidemia, No. (%)1.000
No47 (66.2)48 (67.6)51 (71.8)46 (64.8)
Yes24 (33.8)23 (32.4)20 (28.2)25 (35.2)
Diabetes, No. (%).941
No64 (90.1)55 (77.5)59 (83.1)63 (88.7)
Yes7 (9.9)16 (22.5)12 (16.9)8 (11.3)
Tumor differentiation, No. (%).185
Well12 (16.9)12 (16.9)14 (19.7)15 (21.1)
Moderate40 (56.3)42 (59.2)40 (56.4)44 (62.0)
Poor19 (26.8)17 (23.9)17 (23.9)12 (16.9)
Tumor size, No. (%).097
≤5.0 cm36 (50.7)37 (52.1)47 (66.2)43 (60.6)
>5.0 cm35 (49.3)34 (47.9)24 (33.8)28 (39.4)
Lymph node metastasis, No. (%)<.001
No33 (46.5)50 (70.4)54 (76.1)53 (74.6)
Yes38 (53.5)21 (29.6)17 (23.9)18 (25.4)
TNM stage, No. (%).001
I15 (21.1)21 (29.6)29 (40.9)24 (33.8)
II22 (31.0)24 (33.8)26 (36.6)31 (43.7)
III34 (47.9)26 (36.6)16 (22.5)16 (22.5)
CEA, No. (%).089
Normal26 (36.6)35 (49.3)37 (52.1)36 (50.7)
Abnormal45 (63.4)36 (50.7)34 (47.9)35 (49.3)

Q1: quartile 1, Q2: quartile 2, Q3: quartile 3, Q4: quartile 4. Correlation was determined by linear‐by‐linear association test or Spearman's rank correlation test. CEA, carcinoembryonic antigen.

Correlation analysis between circ_0001946 and clinical characteristics Q1: quartile 1, Q2: quartile 2, Q3: quartile 3, Q4: quartile 4. Correlation was determined by linear‐by‐linear association test or Spearman's rank correlation test. CEA, carcinoembryonic antigen.

Correlation of tumor circ_0001946 expression with patients’ prognosis

Moreover, patients’ recurrence and survival status were acquired, and their DFS and OS were calculated. Data showed that higher tumor circ_0001946 expression was associated with improved DFS (P < .001) (Figure 3A) and OS (P < .001) in NSCLC patients (Figure 3B).
Figure 3

Association between tumor circ_0001946 expression and prognosis in NSCLC patients. (A) Correlation of tumor circ_0001946 with DFS; (B) correlation of tumor circ_0001946 with OS. Circ_0001946, circular RNA_0001946; DFS, disease‐free survival; NSCLC, non‐small‐cell lung cancer; OS, overall survival

Association between tumor circ_0001946 expression and prognosis in NSCLC patients. (A) Correlation of tumor circ_0001946 with DFS; (B) correlation of tumor circ_0001946 with OS. Circ_0001946, circular RNA_0001946; DFS, disease‐free survival; NSCLC, non‐small‐cell lung cancer; OS, overall survival

Subgroup analysis

In addition, the correlation of tumor circ_0001946 expression with prognosis in patients with different TNM stages was analyzed. As to DFS, data revealed that higher TNM stage was associated with worse DFS (P < .001) (Figure 4A); meanwhile, higher tumor circ_0001946 expression was associated with prolonged DFS in patients with TNM stage I (P = .033) (Figure 4B), TNM stage II (P = .015) (Figure 4C), and TNM stage III (P = .028), respectively (Figure 4D). With regard to OS, higher TNM stage was also associated with worse OS (P < .001) (Figure 5A); however, higher tumor circ_0001946 was only associated with increased OS in patients with TNM stage III (P = .037) (Figure 5D), but not in patients with TNM stage I (P = .051) (Figure 5B) or TNM stage II (P = .168) (Figure 5C). These data indicated that circ_0001946 might be a stronger prognostic factor in NSCLC patients with TNM stage III.
Figure 4

Subgroup analysis of the association between tumor circ_0001946 expression and DFS in NSCLC patients with different TNM stages. (A) Correlation of TNM stage with DFS; (B) correlation of tumor circ_0001946 with DFS in patients with TNM stage I; (C) correlation of tumor circ_0001946 with DFS in patients with TNM stage II; and (D) correlation of tumor circ_0001946 with DFS in patients with TNM stage III. Circ_0001946, circular RNA_0001946; DFS, disease‐free survival; NSCLC, non‐small‐cell lung cancer

Figure 5

Subgroup analysis of the association between tumor circ_0001946 expression and OS in NSCLC patients with different TNM stages. (A) Correlation of TNM stage with OS; (B) correlation of tumor circ_0001946 with OS in patients with TNM stage I; (C) correlation of tumor circ_0001946 with OS in patients with TNM stage II; and (D) correlation of tumor circ_0001946 with OS in patients with TNM stage III. Circ_0001946, circular RNA_0001946; NSCLC, non‐small‐cell lung cancer; OS, overall survival

Subgroup analysis of the association between tumor circ_0001946 expression and DFS in NSCLC patients with different TNM stages. (A) Correlation of TNM stage with DFS; (B) correlation of tumor circ_0001946 with DFS in patients with TNM stage I; (C) correlation of tumor circ_0001946 with DFS in patients with TNM stage II; and (D) correlation of tumor circ_0001946 with DFS in patients with TNM stage III. Circ_0001946, circular RNA_0001946; DFS, disease‐free survival; NSCLC, non‐small‐cell lung cancer Subgroup analysis of the association between tumor circ_0001946 expression and OS in NSCLC patients with different TNM stages. (A) Correlation of TNM stage with OS; (B) correlation of tumor circ_0001946 with OS in patients with TNM stage I; (C) correlation of tumor circ_0001946 with OS in patients with TNM stage II; and (D) correlation of tumor circ_0001946 with OS in patients with TNM stage III. Circ_0001946, circular RNA_0001946; NSCLC, non‐small‐cell lung cancer; OS, overall survival

Independent factors for patients’ prognosis

Further multivariate Cox's proportional hazard regression analysis revealed that higher tumor circ_001946 expression (P < .001, HR = 0.719), age > 60 years (P = .033, HR = 0.714), and radiotherapy (P = .016, HR = 0.601) were independently correlated with improved DFS, while hyperlipidemia (P = .020, HR = 1.487), lymph node metastasis (P = .031, HR = 1.479), and higher TNM stage (P = .001, HR = 1.517) were independently correlated with worse DFS (Table 3). Besides, higher tumor circ_0001946 expression was also independently correlated with improved OS (P < .001, HR = 0.746), but hyperlipidemia (P = .002, HR = 1.874), history of drink (P = .022, HR = 1.530), poor tumor differentiation (P = .007, HR = 1.496), and lymph node metastasis (P < .001, HR = 2.945) were independently correlated with reduced OS (Table 4).
Table 3

Analysis for factors correlated with DFS

ItemsForward stepwise multivariate Cox's proportional hazard regression model
P valueHR95%CI
LowerHigher
Higher circ_0001946 expressiona <.0010.7140.6210.820
Age > 60 y.0330.7140.5230.973
Hyperlipidemia.0201.4871.0662.075
Lymph node metastasis.0041.7111.1892.462
Higher TNM stage<.0011.6201.2682.072
RT.0160.6010.3970.910

Factors correlated with DFS were analyzed by forward stepwise multivariate Cox's proportional hazard regression model.

Abbreviations: CI, confidence interval; DFS, disease‐free survival, HR, hazard ratio; RT, radiotherapy.

circ_0001946 expression was categorized as 0%‐25% quartile = 0, 25%‐50% quartile = 1, 50%‐75% quartile = 2, and 75%‐100% quartile = 3.

Table 4

Analysis for factors correlated with OS

ItemsForward stepwise multivariate Cox's proportional hazard regression model
P valueHR95%CI
LowerHigher
Higher circ_0001946 expressiona <.0010.7240.6150.851
History of drink.0301.4981.0402.157
Hyperlipidemia.0021.8741.2662.773
Poor tumor differentiation.0011.6201.2082.173
Lymph node metastasis<.0013.1352.1604.550

Factors correlated with OS were analyzed by forward stepwise multivariate Cox's proportional hazard regression model.

Abbreviations: CI, confidence interval; HR, hazard ratio;OS, overall survival.

circ_0001946 expression was categorized as 0%‐25% quartile = 0, 25%‐50% quartile = 1, 50%‐75% quartile = 2, and 75%‐100% quartile = 3.

Analysis for factors correlated with DFS Factors correlated with DFS were analyzed by forward stepwise multivariate Cox's proportional hazard regression model. Abbreviations: CI, confidence interval; DFS, disease‐free survival, HR, hazard ratio; RT, radiotherapy. circ_0001946 expression was categorized as 0%‐25% quartile = 0, 25%‐50% quartile = 1, 50%‐75% quartile = 2, and 75%‐100% quartile = 3. Analysis for factors correlated with OS Factors correlated with OS were analyzed by forward stepwise multivariate Cox's proportional hazard regression model. Abbreviations: CI, confidence interval; HR, hazard ratio;OS, overall survival. circ_0001946 expression was categorized as 0%‐25% quartile = 0, 25%‐50% quartile = 1, 50%‐75% quartile = 2, and 75%‐100% quartile = 3.

DISCUSSION

CircRNAs have aroused the interest of researches during the past few years., As a newly discovered circRNA, circ_0001946 presents regulation on several tumors. For example, in glioblastoma, circ_0001946 overexpression suppresses cell proliferation, migration, and invasion through targeting microRNA (miR)‐671‐5p, and in vivo experiments further verify these findings. Meanwhile, in colorectal cancer, circ_0001946 also regulates cell proliferation, migration, and invasion through modifying the epithelial‐mesenchymal transition (EMT) pathway. In addition, in NSCLC, circ_0001946 knockdown promotes cell proliferation, migration, invasion, and the sensitivity to cisplatin through modulating the nucleotide excision repair (NER) pathway. Therefore, circ_0001946 not only critically regulates the progression, but also plays an important role in the chemosensitivity of several tumors, including NSCLC. Several previous studies have reported the dysregulation of circ_0001946 in tumor tissues. For instance, it is suggested that circ_0001946 is downregulated in the tumor tissues compared to the non‐tumor tissues in esophageal squamous cell cancer patients. Besides, another study reveals that circ_0001946 is also reduced in the tumor tissues compared to the paired non‐cancerous tissues in bladder cancer patients. However, circ_0001946 relative expression in NSCLC patients is largely unclear. In the present study, we analyzed the 284 NSCLC tumor tissues and 125 adjacent non‐tumor tissues, and found that circ_0001946 was downregulated in the tumor tissues compared to the adjacent tissues of NSCLC patients, which was in line with a previous study. Possible explanations for our data might be that (a) circ_0001946 low expression might activate the NER pathway to directly increase the incidence of NSCLC; (b) as a competing endogenous circRNA, circ_0001946 low expression might increase several miRNAs that could promote tumorigenesis, such as miR‐671‐5p (as in glioblastoma), thus indirectly promoted the incidence of NSCLC. Therefore, circ_0001946 was reduced in tumor tissues compared to adjacent non‐cancerous tissues in NSCLC patients. Regarding the correlation of circ_0001946 with tumor characteristics, one interesting previous study suggests that circ_0001946 dysregulation is negatively correlated with tumor size, histologic grade, lymphatic metastasis, and TMN stage in colorectal cancer patients. In the present study, data showed that higher tumor circ_0001946 expression was associated with less lymph node metastasis and lower TNM stage. Our data could be explained by that (a) higher circ_0001946 might suppress the epithelial‐mesenchymal transition to promote the migration and invasion ability of NSCLC cells, thus decreasing its metastatic potential (as in colorectal cancer). Therefore, higher circ_0001946 was correlated with less lymph node metastasis in NSCLC patients; (b) higher circ_0001946 expression might reduce the level of several miRNAs that promote the progression of cancers, such as miR‐671‐5p (as in glioblastoma), thus suppressing NSCLC cell proliferation, migration, and invasion, and resulting in lower TNM stage. Identifying potential prognostic biomarkers might improve the management toward NSCLC patients, thus ameliorating their overall prognosis., Meanwhile, the prognostic value of circ_0001946 has been reported by previous studies. For example, circ_0001946 dysregulation could be an indicator of worse prognosis in bladder cancer patients and esophageal squamous cell cancer patients. However, the prognostic value of circ_0001946 in NSCLC patients is not clear. In the present study, we found that higher tumor circ_0001946 was correlated with improved DFS and OS in NSCLC patients. Meanwhile, subgroup analysis revealed that higher tumor circ_0001946 was further correlated with improved DFS in NSCLC patients with TNM stage I, II, or III; while it was only correlated with increased OS in patients with TNM stage III, but not in patients with TNM stage I or II, implying circ_0001946 might had a stronger prognostic effect in patients with TNM stage III, which may be explained by its influence on the sensitivity to postoperative adjuvant chemotherapy in NSCLC patients with TNM stage III, thus further affecting their prognosis. Moreover, multivariate Cox's proportional hazard regression analyses suggested that higher circ_0001946 expression was an independent factor for both improved DFS and OS. Our data could be explained by that (a) higher tumor circ_0001946 was correlated with less lymph node metastasis and lower TNM stage (mentioned above), which directly resulted in favorable prognosis in NSCLC patients; (b) higher tumor circ_0001946 might suppress the NER pathway to increase the chemosensitivity of NSCLC cells, which resulted in better treatment effect of chemotherapeutic agents, thus indirectly caused improved prognosis in NSCLC patients. Further studies were encouraged to explore the correlation of the parent gene of circ_0001946 with the tumor features and prognosis of NSCLC patients. Although we had found some interesting results, there existed several limitations in this study. First, NSCLC patients who were unsuitable to undergo resection were not included in this study, and these results could not be applied in them; thus, further studies could be conducted to investigate the role of circ_0001946 in these patients when the tissue samples were available. Second, although we had enrolled 284 NSCLC patients, the sample size was still not big enough and might cause low statistical power, especially in the subgroup analysis of the correlation of tumor circ_0001946 with the prognosis of patients with TNM stage I, II, or III. Third, the long‐term prognostic value of circ_0001946 in NSCLC patients was not investigated, which could be conducted further. Fourth, this study was a retrospective study, which might cause selection bias, and further prospective study could be conducted. To be conclusive, circ_0001946 is reduced in tumor tissues, while its higher expression correlates with reduced lymph node metastasis, decreased TNM stage, and improved prognosis in NSCLC patients.
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Journal:  Int J Tuberc Lung Dis       Date:  2004-09       Impact factor: 2.373

8.  Downregulated hsa_circ_0077837 and hsa_circ_0004826, facilitate bladder cancer progression and predict poor prognosis for bladder cancer patients.

Authors:  Chong Shen; Zhouliang Wu; Yujie Wang; Shen Gao; Linguo Xie; Yunkai Qie; Dawei Tian; Hailong Hu
Journal:  Cancer Med       Date:  2020-04-06       Impact factor: 4.452

9.  Circular RNA profiling and its potential for esophageal squamous cell cancer diagnosis and prognosis.

Authors:  Liyuan Fan; Qiang Cao; Jia Liu; Junpeng Zhang; Baosheng Li
Journal:  Mol Cancer       Date:  2019-01-23       Impact factor: 27.401

10.  Dysregulation of CircRNA_0001946 Contributes to the Proliferation and Metastasis of Colorectal Cancer Cells by Targeting MicroRNA-135a-5p.

Authors:  Zhenwei Deng; Xiyao Li; Huaiming Wang; Yongyong Geng; Yongchang Cai; Yuxin Tang; Yijun Wang; Xueqiao Yu; Libo Li; Ruiping Li
Journal:  Front Genet       Date:  2020-05-08       Impact factor: 4.599

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  6 in total

1.  Dysregulated circular RNAs are closely linked to multiple myeloma prognosis, with circ_0026652 predicting bortezomib‑based treatment response and survival via the microRNA‑608‑mediated Wnt/β‑catenin pathway.

Authors:  Lu Li; Jin Liu; Juan Du; Hua Jiang; Haiyan He; Jing Lu; Wanting Qiang; Nan Hou; Pei Guo; Yan Zhuang; Weijun Fu
Journal:  Oncol Rep       Date:  2022-09-21       Impact factor: 4.136

Review 2.  Role of circular RNAs in the diagnosis, regulation of drug resistance and prognosis of lung cancer.

Authors:  Chengpeng Sang; Dingyu Rao; Caixia Wu; Yao Xia; Maoyan Si; Zhixian Tang
Journal:  Oncol Lett       Date:  2022-07-07       Impact factor: 3.111

3.  Whole Transcriptome Analysis Identifies Platycodin D-Mediated RNA Regulatory Network in Non-Small-Cell Lung Cancer.

Authors:  Shuyu Zheng; Zejuan Xie; Yanlin Xin; Wenli Lu; Hao Yang; Tianming Lu; Jun Li; Shanshan Wang; Keyu Cheng; Xi Yang; Ruogu Qi; Yongming Qiu; Yuanyuan Guo
Journal:  Cells       Date:  2022-08-01       Impact factor: 7.666

4.  Calycosin Inhibits the Malignant Behaviors of Lung Adenocarcinoma Cells by Regulating the circ_0001946/miR-21/GPD1L/HIF-1α Signaling Axis.

Authors:  Lixia Zhou; Wenxian Chen; Hang Yang; Jiaqin Liu; Hui Meng
Journal:  Dis Markers       Date:  2022-08-13       Impact factor: 3.464

5.  hsa_circ_0003176 Suppresses the Progression of Non-Small-Cell Lung Cancer via Regulating miR-182-5p/RBM5 Axis.

Authors:  Fangfang Yang; YanLi Pei; Wei Xu; Lei Rong
Journal:  Dis Markers       Date:  2022-09-23       Impact factor: 3.464

6.  Circular RNA_0001946 is insufficiently expressed in tumor tissues, while its higher expression correlates with less lymph node metastasis, lower TNM stage, and improved prognosis in NSCLC patients.

Authors:  Minghua Zhang; Fangjing Wen; Ke Zhao
Journal:  J Clin Lab Anal       Date:  2021-07-03       Impact factor: 2.352

  6 in total

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