
==== Front
Eur J Med Res
Eur J Med Res
European Journal of Medical Research
0949-2321
2047-783X
BioMed Central London

2015
10.1186/s40001-024-02015-y
Research
Value of CDR1-AS as a predictive and prognostic biomarker for patients with breast cancer receiving neoadjuvant chemotherapy in a prospective Chinese cohort
Yuan Chenwei 1
Xu Yaqian 2
Zhou Liheng kaneshiro_lily@hotmail.com

1
Peng Jing 1
Sha Rui 1
Lin Yanping 1
Xu Shuguang 1
Ye Yumei 1
Yang Fan 1
Yan Tingting 1
Dong Xinrui 1
Wang Yaohui wangyaohui@renji.com

1
Yin Wenjin 1
Lu Jinsong lujingsong@renji.com

1
1 grid.16821.3c 0000 0004 0368 8293 Present Address: Department of Breast Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, No. 160 Pujian Road, Shanghai, 200127 People’s Republic of China
2 https://ror.org/035adwg89 grid.411634.5 0000 0004 0632 4559 Breast Center, Peking University People’s Hospital, No.11 Xizhimen Southern Street, Beijing, 100044 People’s Republic of China
11 9 2024
11 9 2024
2024
29 4548 5 2023
6 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Background

Neoadjuvant chemotherapy (NAC) is an effective treatment for locally advanced breast cancer (BC). However, there are no effective biomarkers for evaluating its efficacy. CDR1-AS, well known for its important role in tumorigenesis, is a famous circular RNA involved in the chemosensitivity of cancers other than BC. However, the predictive role of CDR1-AS in the efficacy and prognosis of NAC for BC has not been fully elucidated. We herein aimed to clarify this role.

Methods

The present study included patients treated with paclitaxel-cisplatin-based NAC. The expression of CDR1-AS was detected by real-time quantitative reverse transcription polymerase chain reaction testing. The predictive value of CDR1-AS expression was examined in pathological complete response (pCR) after NAC using logistic regression analysis. The relationship between CDR1-AS expression and survival was demonstrated using the Kaplan–Meier method, and tested by log-rank test and Cox proportional hazards regression model.

Results

The present study enrolled 106 patients with BC. Multivariate logistic regression analysis revealed that CDR1-AS expression was an independent predictive factor for pCR (odds ratio [OR] = 0.244; 95% confidence interval [CI] 0.081–0.732; p = 0.012). Furthermore, pCR benefits with low CDR1-AS expression were observed across all subgroups. The Kaplan–Meier curves and log-rank test suggested that the CDR1-AS high-expression group showed significantly better disease-free survival (DFS; log-rank p = 0.022) and relapse-free survival (RFS; log-rank p = 0.012) than the CDR1-AS low-expression group. Multivariate analysis revealed that CDR1-AS expression was an independent prognostic factor for DFS (adjusted HR = 0.177; 95% CI 0.034–0.928, p = 0.041), RFS (adjusted HR = 0.061; 95% CI 0.006–0.643, p = 0.020), and distant disease-free survival (adjusted HR = 0.061; 95% CI 0.006–0.972, p = 0.047).

Conclusions

CDR1-AS may be a potential novel predictive biomarker of pCR and survival benefit in patients with locally advanced BC receiving NAC. This may help identify specific chemosensitive individuals and build personalized treatment strategies.

Keywords

Biomarker
Breast cancer
Circular RNA
CDR1-AS
Neoadjuvant chemotherapy
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
==== Body
pmcIntroduction

Breast cancer (BC) is a major cause of cancer-related death among women, becoming the most common malignant tumor worldwide [1]. Locally advanced breast cancer (LABC) is a huge clinical challenge because most patients with LABC experience a high recurrence rate and shorter survival compared to those with not advanced tumors. Neoadjuvant therapy is a commonly used and effective treatment because it can render inoperable tumors resectable and improve breast conservation rates [2]. Moreover, neoadjuvant chemotherapy (NAC) can identify individuals at high risk of recurrence who may have residual tumors for subsequent intensive adjuvant therapy, especially for triple-negative and human epidermal growth factor receptor 2 (HER2)-positive BC. Several large clinical trials have confirmed that patients with BC who achieve pathological complete response (pCR) after NAC have a significantly better prognosis than those who do not [3–5]. However, there are currently no effective biomarkers that can accurately predict the pCR of BC after NAC. Thus, there is an urgent need to discover effective biomarkers to determine the efficacy of NAC for BC.

Circular RNA (circRNA) is a newly discovered type of non-coding RNA with a covalent closed loop structure without a 5′-cap structure or 3′-polyadenylation tail in recent years. CircRNAs can regulate gene expression at epigenetic, transcriptional, and post-transcriptional levels and affect tumorigenesis through diverse mechanisms of action and functional roles, including microRNA sponging, protein interaction, translation, and so on [6]. Given their high stability and detectability in human tissues and biofluids, circRNAs have been recognized as promising diagnostic and prognostic biomarkers. CDR1-AS (hsa_circ_0001946), a naturally occurring RNA transcribed in antisense to CDR1, which is located on the human chromosome Xq27.1 region, plays various roles through different functions in tumors [7–9]. Piwecka conducted an analysis of CDR1-AS expression across various mouse tissues, revealing that it is most prominently expressed in neural tissues, abundant expressed in spinal cord, low expressed in lung tissue, skeletal muscle and heart, and almost undetectable in spleen, suggesting a distinct pattern of tissue-specific expression for CDR1-AS [10]. Growing evidence indicates that circRNAs are highly relevant to drug resistance and metabolism. Yang et al. found that CDR1-AS increased the resistance of BC cells to 5-FU chemotherapy. The main mechanism is that inhibiting the expression of CDR1-AS can upregulate the expression of miR-7, thus suppressing the expression of CCNE1 and finally improving the chemotherapy sensitivity of 5-FU resistant BC cells [11]. Another study by Yang et al. revealed that CDR1-AS increased the resistance of BC cells to cisplatin chemotherapy. The main mechanism is that the overexpression of CDR1-AS acts as a molecular sponge to adsorb miR-7, thus upregulating REGγ, which is related to poor prognosis of BC and further leads to the resistance of BC cells to cisplatin [12]. To the best of our knowledge, circRNAs such as CDR1-AS have not been put into practice as biomarkers in clinical decision-making, and proper validation studies involving prospectively collected samples and clinical trials are lacking. The role of CDR1-AS in predicting the efficacy of NAC in patients with BC remains unknown.

Accordingly, this study aimed to evaluate the predictive role of CDR1-AS in the efficacy and prognosis of NAC for BC. We hypothesized that the expression of CDR1-AS might help predict neoadjuvant chemosensitivity in patients with BC, which was illustrated in this retrospective study on our prospective clinical trials.

Materials and methods

Patients and study design

The patients enrolled in the two registered prospective neoadjuvant clinical trials SHPD001 (NCT02199418) and SHPD002 (NCT02221999) were analyzed in this study. The research protocols of both clinical trials were approved by the Independent Ethics Committee of Renji Hospital, School of Medicine, Shanghai Jiaotong University. Written informed consent was obtained from all patients. In total, 106 patients (SHPD001 trial, N = 3; SHPD002 trial, N = 103) with adequate and qualified tissue samples for the detection of CDR1-AS expression from the aforementioned trials were enrolled in this study.

The treatment protocols have been reported previously [13]. Patients were all qualified with the following inclusion criteria: women aged 18–70 years old, histologically confirmed invasive BC with a tumor size ≥ 2 cm, no prior systemic or loco-regional treatment administered to patients, and sufficient and eligible tissue samples for CDR1-AS expression detection. The NAC regimens were as follows: patients received four cycles of treatment for 28 days per cycle. For every cycle, paclitaxel (80 mg/m2) was administered weekly on days 1, 8, 15, and 22, and cisplatin (25 mg/m2) was administered on days 1, 8, and 15. HER2-positive patients concomitantly received trastuzumab. For patients with ER-or PR-positive BC in SHPD002, endocrine therapy with letrozole in postmenopausal women and ovarian function suppression in premenopausal women were randomized together with chemotherapy, according to their menopausal status. Premenopausal patients with triple-negative BC were randomized to chemotherapy with or without ovarian function suppression in SHPD002. The patients underwent surgery sequentially after completing neoadjuvant therapy.

Tissue samples and clinical data collection

Clinical data was collected prospectively when patients were enrolled in the clinical trial (Table 1). Fresh primary cancer tissue specimens were collected from the Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University. The tissues were collected by core-needle biopsy before the patients underwent neoadjuvant treatment, frozen immediately in liquid nitrogen, and stored at − 80 °C until RNA extraction. Positive status of estrogen receptor (ER) and progesterone receptor (PR) was defined as ≥ 1% of tumor cells showing positive nuclear staining by immunohistochemistry (IHC). HER2 positivity was defined as IHC 3 + or fluorescence in situ hybridization positivity [14]. Table 1 Associations between CDR1-AS expression level and baseline clinicopathological characteristics

Characteristics	CDR1-AS low (n = 53)	CDR1-AS high (n = 53)	p value	
Age (years)			0.166	
 ≤ 50	18 (33.96%)	25 (47.17%)		
 > 50	35 (66.04%)	28 (52.83%)		
Median age at surgery (range)	56 (31–70)	52 (26–69)		
Menopausal status			0.077	
 pre-menopausal	18 (33.96%)	27 (50.94%)		
 post-menopausal	35 (66.04%)	26 (49.06%)		
BMI			0.430	
 < 24	29 (54.72%)	33 (62.26%)		
 ≥ 24	24 (45.28%)	20 (37.74%)		
Clinical T stage			0.113	
 T2	10 (18.87%)	9 (16.98%)		
 T3	22 (41.51%)	32 (60.38%)		
 T4	21 (39.62%)	12 (22.64%)		
Clinical N stage			0.184	
 N0	3(5.66%)	7(13.21%)		
 N1-N3	50(94.34%)	46(86.79%)		
ER status			0.636	
 Negative	21 (39.62%)	23 (43.40%)		
 Positive	32 (60.38%)	30 (56.60%)		
PR status			0.541	
 Negative	20 (37.74%)	17 (32.08%)		
 Positive	33 (62.26%)	36 (67.92%)		
HER2 status			0.695	
 Negative	29 (54.72%)	31 (58.49%)		
 Positive	24 (45.28%)	22 (41.51%)		
Ki67 index			0.43	
 ≤ 30%	20 (37.74%)	24 (45.28%)		
 > 30%	33 (62.26%)	29 (54.72%)		
Histological grade			0.152	
 II	13 (24.53%)	19 (35.85%)		
 III	37 (69.81%)	29 (54.72%)		
 Unknown	3 (5.66%)	5 (9.43%)		
pCR			0.154	
 No	31 (58.49%)	38 (71.70%)		
 Yes	22 (41.51%)	15 (28.30%)		
The p values are calculated using the chi-squared test.

BMI body mass index, Clinical T stage Clinical tumor stage, Clinical N stage Clinical nodal stage, ER estrogen receptor, PR progesterone receptor, HER2 human epidermal growth factor receptor 2, pCR pathologic complete response

RNA extraction and real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) testing

Total RNA from BC tissues was extracted with a TRIzol reagent (Invitrogen, NY, USA) and subsequently reverse-transcribed into cDNA using PrimeScript™ RT Master Mix (Perfect Real Time; Takara, Shiga, Japan) according to the manufacturer’s instructions. qRT-PCR testing was performed using SYBR® Premix Ex TaqTM (Tli RNaseH Plus; Takara) in a LightCycler® 480 System (Roche, Basel, Switzerland) according to the manufacturer’s protocol. The specific primers used were as follows: CDR1-AS sense 5′-ACGTCTCCAGTGTGCTGA-3′ and antisense 5′-CTTGACACAGGTGCCATC-3′,  and β-actin sense 5′-CATGTACGTTGCTATCCAGGC-3′ and antisense 5′-CTCCTTAATGTCACGCACGAT-3′. β-Actin was used as an internal control, and gene expression levels were normalized to β-actin using the 2−ΔCt method [15]. Each reaction was performed in triplicates.

In silico analysis

The pan-cancer analysis of CDR1-AS expression was shown based on the MiOncoCirc database (N = 744; http://mioncocirc.github.io/; access on June 30, 2022) [16]. The comparison of CDR1-AS expression was performed between BC tissues (N = 1085) and normal breast tissues (N = 112) and tested by student’s t-test within the GEPIA database (http://gepia.cancer-pku.cn/; access on June 30, 2022) [17].

Statistical analyses

Patients were divided into the high- and low-expression cohorts according to the median expression of CDR1-AS. The relationship between all baseline clinicopathological characteristics and CDR1-AS expression levels was calculated using the chi-squared test. Univariate and multivariate binary logistic regression analyses were utilized to evaluate the association between CDR1-AS expression or clinical characteristics and pCR and investigate the potential interactions between CDR1-AS expression and clinical characteristics of pCR. A nomogram was constructed to predict pCR by combining CDR1-AS with clinical attributes, including clinical T stage, ER status, and HER2 status. A calibration curve was used to evaluate nomogram calibration. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were performed to examine whether CDR1-AS could improve the ability to predict a patient’s response to NAC. The Kaplan–Meier method was used to calculate the survival rates, and survival curves were compared using the log-rank test. Univariate and multivariate Cox proportional hazards models were used to investigate independent risk factors for disease-free survival (DFS), relapse-free survival (RFS), and distant disease-free survival (DDFS). DFS was defined as the time from surgery to the first recurrence (local, regional, distant), contralateral BC, second primary non-breast cancer, or death from any cause. RFS was defined as the time from surgery to local, regional, or distant relapse or death. DDFS was defined as the time from surgery to distant recurrence or death. All statistical analyses were performed using Stata version 14.1 (Stata Corp LLC, Texas, USA) and R software version 3.6.1 (www.r-project.org). A p-value < 0.05 was considered statistically significant.

Results

CDR1-AS expression and baseline characteristics

The relative CDR1-AS expression in pan-cancer tissues was analyzed based on the MiOncoCirc database [16] and was found abundant in BRCA group (breast invasive carcinoma) (Fig. 1A). The relative expression of CDR1-AS in BC was higher than other common cancers, such as lung cancer and hepatocellular carcinoma, which were leading fatal cancer types in China. The expression of CDR1-AS was explored in the GEPIA database [17] and was found to be significantly downregulated in BC tissues compared to that in normal breast tissues (p < 0.01) (Fig. 1B). A total of 106 patients were included in this study and divided into two groups based on the median expression of CDR1-AS. Thus, both the high and low CDR1-AS expression groups included 53 patients. No significant differences were found in clinico-histopathological characteristics, including age, body mass index (BMI), ER status, PR status, and other factors, between the high and low CDR1-AS expression group (Table 1). Thirty-seven patients achieved pCR, and the total pCR rate was 34.91%. Thirteen events occurred in this cohort: one patient died, ten relapsed or progressed, and two had secondary primary cancer.Fig. 1 CDR1-AS expression in cancer tissues. A Relative CDR1-AS expression in pan-cancer tissues based on the MiOncoCirc database. B Relative CDR1-AS expression in BC and normal tissues based on the GEPIA database. *p < 0.01 (student’s t-test). ACC adrenocortical carcinoma, BLCA bladder urothelial carcinoma, BRCA breast invasive carcinoma, CHOL cholangiocarcinoma, ESCA esophageal carcinoma, GBM Glioblastoma multiforme, HCC hepatocellular carcinoma, HNSC head and neck squamous cell carcinoma, KDNY kidney cancer, LUNG lung cancer, MBL medulloblastoma, NRBL neuroblastoma, OV ovarian serous cystadenocarcinoma, PAAD pancreatic adenocarcinoma, PRAD prostate adenocarcinoma, SARC sarcoma, SECR secretory cancer, and SKCM skin cutaneous melanoma

CDR1-AS expression and pCR outcomes

The median CDR1-AS expression was 0.099 (range, 0.017 to 1.149) and 0.091 (range, 0.002 to 0.614) in the pCR and non-pCR group, respectively (Fig. 2A). Patients with low CDR1-AS expression achieved a higher pCR rate (41.51%) than those with high CDR1-AS expression (28.30%; Fig. 2B), although the difference was not significant (odds ratio [OR] = 0.556; 95% confidence interval [CI] 0.247–1.250, p = 0.156; Table 2). In univariate logistic regression analysis, negative ER status (OR = 0.182; 95% CI 0.077–0.434, p < 0.001) and positive HER2 status (OR = 3.286; 95% CI 1.430–7.549, p < 0.001) favored pCR. Moreover, negative PR status (OR = 0.480; 95% CI 0.209–1.101, p = 0.083) and low BMI status (OR = 0.462; 95% CI 0.197–1.078, p = 0.074) tended to favor pCR. Age (OR = 1.191; 95% CI 0.525–2.700, p = 0.675), clinical tumor stage (OR = 0.486; 95% CI 0.193–1.223, p = 0.125) and ki67 status (OR = 1.506; 95% CI 0.660–3.437, p = 0.331) were not significantly associated with pCR (Table 2).Fig. 2 Features of patients with pathological complete response (pCR) and non-pCR. A The relative CDR1-AS expression in the pCR and non-pCR group. B Clinicopathological features of pCR and no-pCR patients. Two-category data (pCR, yes vs. no; CDR1-AS expression, high vs. low; age, ≥ 50 vs. < 50 years, clinical T-stage, T4 vs. T2–3; clinical N stage, N1–3 vs. N0; ER positivity vs. negativity; PR positivity vs. negativity; HER2 positivity vs. negativity; Ki67 > 30% vs. ≤ 30%; and BMI ≥ 24 vs. < 24 kg/m2) are shown in dark and light blue, respectively. pCR pathological complete response, ER estrogen receptor, PR progesterone receptor, HER2 human epidermal growth factor receptor 2, and BMI body mass index

Table 2 Univariate and multivariate binary logistic regression analyses of CDR1-AS expression or clinical characteristics and pathological complete response to neoadjuvant therapy

Variable	Categories	Univariate	Multivariate	
OR	95% CI	p	OR	95% CI	p	
Age	 > 50, ≤ 50	1.191	0.525–2.700	0.675	0.677	0.231–1.980	0.476	
Clinical T stage	T4, T2-T3	0.486	0.193–1.223	0.125	0.123	0.029–0.518	0.004*	
ER status	Positive, negative	0.182	0.077–0.434	0.000*	0.101	0.027–0.375	0.001*	
PR status	Positive, negative	0.480	0.209–1.101	0.083	1.141	0.341–3.820	0.831	
HER2 status	Positive, negative	3.286	1.430–7.549	0.005*	6.668	2.085–21.328	0.001*	
Ki67 index	 > 30, ≤ 30	1.506	0.660–3.437	0.331	0.667	0.214–2.080	0.485	
BMI	 ≥ 24, < 24	0.462	0.197–1.078	0.074	0.326	0.105–1.026	0.055	
CDR1-AS	High, low	0.556	0.247–1.250	0.156	0.244	0.081–0.732	0.012*	
Clinical T stage Clinical tumor stage, ER estrogen receptor, PR progesterone receptor, HER2 human epidermal growth factor receptor 2, BMI body mass index

After adjusting for age, clinical tumor stage, ER status, PR status, HER2 status, Ki67 index, and BMI status, multiple logistic regression analysis revealed that low CDR1-AS expression was significantly associated with pCR (OR = 0.244; 95% CI 0.081–0.732, p = 0.012). Meanwhile, patients with lower clinical tumor stage (OR = 0.123; 95% CI 0.029–0.518, p = 0.004), negative ER status (OR = 0.101; 95% CI 0.027–0.375, p = 0.001), and positive HER2 status (OR = 6.668; 95% CI 2.085–21.328, p = 0.001) could achieve pCR more easily (Table 2).

Building and assessment of the multivariate model for pCR prediction

According to prior multiple logistic regression analysis, four predictive features, including clinical T stage, ER status, HER2 status, and CDR1-AS, were selected to build a multivariate predictive model. A nomogram was created for predicting pCR (Fig. 3A). The calibration curves showed a high consistency between the prediction of the nomogram and the actual observed pCR outcomes in our cohort (Fig. 3B). ROC curves and DCA were used to compare the accuracy of different predictive models with or without CDR1-AS. The area under the curve (AUC) was 0.813 (95% CI 0.727–0.898), achieved by adding CDR1-AS to clinicopathological features, which is better than 0.789 (95% CI 0.700–0.877) for clinicopathological characteristics alone (Fig. 3C). Moreover, DCA consistently showed more benefits with the model combining CDR1-AS with clinicopathological variables (Fig. 3D).Fig. 3 Nomogram of the multivariate model for pCR prediction A The nomogram was built using independent predictive factors for pCR. B Calibration curve of nomogram. C Receiver operating characteristic curves of the predictive models with and without CDR1-AS expression (area under the curve, 0.813 vs. 0.789). D Decision curve analysis of the net benefit versus threshold probability. ER estrogen status, HER2 human epidermal growth factor receptor 2, and pCR pathological complete response

Subgroup analysis of pCR rates

Subgroup analysis suggested that pCR outcomes were significantly associated with CDR1-AS in patients aged ≥ 50 years (OR = 0.096; 95% CI 0.013–0.709; p = 0.022) and those with a BMI less than 24 (OR = 0.172; 95% CI 0.038–0.780; p = 0.022), as well as premenopausal (OR = 0.163; 95% CI; 0.027–0.988; p = 0.048), postmenopausal (OR = 0.090; 95% CI 0.010–0.787; p = 0.030), T2-3 (OR = 0.244; 95% CI 0.068–0.880; p = 0.031), stage N1–3 (OR = 0.186; 95% CI 0.055–0.631; p = 0.007), ER-negative (OR = 0.131; 95% CI 0.021–0.805, p = 0.028), PR-negative (OR = 0.072; 95% CI 0.009–0.584; p = 0.014), HER2-positive (OR = 0.156; 95% CI 0.026–0.945; p = 0.043), and ki67 > 30% tumors (OR = 0.133; 95% CI 0.024–0.732, p = 0.020; Fig. 4). No interaction was detected between the clinicopathological variables and CDR1-AS for pCR (Fig. 4).Fig. 4 Subgroup analysis for pCR according to CDR1-AS expression levels pCR pathological complete response, OR odds ratio, CI confidence interval, ER estrogen receptor, PR progesterone receptor, HER2 human epidermal growth factor receptor 2, and BMI body mass index

CDR1-AS expression and DFS

The median follow-up time for all patients was 30.02 months. Kaplan–Meier curves and log-rank tests were performed to determine DFS according to CDR1-AS expression level. Compared to the CDR1-AS low-expression group, the high-expression group showed significantly better DFS (N = 106; log-rank p = 0.022; Fig. 5A).Fig. 5 Kaplan–Meier plot estimates of survival outcomes according to CDR1-AS expression levels A DFS was estimated using the Kaplan–Meier plot. B RFS estimated using the Kaplan–Meier plot. C DDFS estimated using the Kaplan–Meier plot. DFS disease-free survival, RFS relapse-free survival, DDFS distant disease-free survival, HR hazard ratio, and CI confidence interval

In the univariate analysis, patients with high expression of CDR1-AS had a substantially better DFS than those with a low expression of CDR1-AS (hazard ratio [HR] = 0.202; 95% CI 0.044–0.924; p = 0.039). Simultaneously, multivariate analysis showed that CDR1-AS expression was an independent prognostic factor for DFS (adjusted HR = 0.177; 95% CI 0.034–0.928, p = 0.041). Moreover, T4 clinical tumor stage (adjusted HR = 5.445; 95% CI 1.294–22.907; p = 0.021) and high ki67 index (adjusted HR = 7.576; 95% CI 1.436–39.973; p = 0.017) were significantly associated with worse DFS (Table 3). Table 3 Univariate and multivariate analysis for CDR1-AS expression or clinicopathological characteristics and disease-free survival (DFS)

Variable	Categories	Univariate	Multivariate	
HR	95% CI	p	HR	95% CI	p	
Age	 > 50, ≤ 50	0.614	0.197–1.913	0.400	0.285	0.075–1.076	0.064	
Clinical T stage	T4, T2-T3	2.491	0.800–7.752	0.115	5.445	1.294–22.907	0.021*	
ER status	Positive, negative	0.661	0.213–2.052	0.474	0.544	0.135–2.193	0.392	
PR status	Positive, negative	0.968	0.291–3.217	0.957	1.148	0.263–5.004	0.854	
HER2 status	Positive, negative	2.147	0.676–6.819	0.195	2.074	0.599–7.176	0.249	
Ki67 index	 > 30, ≤ 30	3.598	0.787–16.445	0.099	7.576	1.436–39.973	0.017*	
BMI	 ≥ 24, < 24	1.607	0.517–4.997	0.412	1.526	0.439–5.303	0.506	
CDR1-AS	High, low	0.202	0.044–0.924	0.039*	0.177	0.034–0.928	0.041*	
Clinical T stage Clinical tumor stage, ER estrogen receptor, PR progesterone receptor, HER2 human epidermal growth factor receptor 2, BMI body mass index

CDR1-AS expression and RFS

The CDR1-AS high-expression group showed significantly better RFS than the low-expression group (N = 106; log-rank p = 0.012; Fig. 5B). In the univariate analysis, patients with high CDR1-AS expression had substantially better RFS than those with low CDR1-AS expression (HR = 0.112; 95% CI 0.014–0.887; p = 0.038). Multivariate analysis showed that CDR1-AS expression was an independent prognostic factor for RFS (adjusted HR = 0.061; 95% CI 0.006–0.643; p = 0.020). Moreover, T4 clinical tumor stage (adjusted HR = 11.078; 95% CI 2.074–59.164; p = 0.005) and high ki67 index (adjusted HR = 9.880; 95% CI 1.666–58.574; p = 0.012) were significantly associated with worse RFS (Table 4). Table 4 Univariate and multivariate analysis for CDR1-AS expression or clinicopathological characteristics and relapse-free survival (RFS)

Variable	Categories	Univariate	Multivariate	
HR	95% CI	p	HR	95% CI	p	
Age	 > 50, ≤ 50	0.976	0.274–3.473	0.970	0.329	0.070–1.552	0.160	
Clinical T stage	T4, T2-T3	3.960	1.112–14.100	0.034*	11.078	2.074–59.164	0.005*	
ER status	Positive, negative	0.669	0.194–2.314	0.526	0.578	0.102–3.266	0.535	
PR status	Positive, negative	0.692	0.195–2.456	0.569	0.921	0.158–5.362	0.927	
HER2 status	Positive, negative	2.282	0.637–8.177	0.205	2.046	0.500–8.364	0.319	
Ki67 index	 > 30, ≤ 30	2.753	0.584–12.981	0.201	9.880	1.666–58.574	0.012*	
BMI	 ≥ 24, < 24	1.027	0.290–3.647	0.966	0.692	0.164–2.930	0.617	
CDR1-AS	High, low	0.112	0.014–0.887	0.038*	0.061	0.006–0.643	0.020*	
Clinical T stage Clinical tumor stage, ER estrogen receptor, PR progesterone receptor, HER2 human epidermal growth factor receptor 2, BMI body mass index

CDR1-AS expression and DDFS

The CDR1-AS high-expression group was prone to have a better DDFS than the low-expression group (N = 106; log-rank p = 0.050; Fig. 5C). In univariate analysis, patients with high expression of CDR1-AS tended to have a better DDFS than patients with low expression of CDR1-AS (HR = 0.158; 95% CI 0.019–1.317; p = 0.088). Multivariate analysis revealed that CDR1-AS expression was an independent prognostic factor for DDFS (adjusted hazard ratio [HR] = 0.061; 95% confidence interval [CI] 0.006–0.972, p = 0.047). Furthermore, T4 clinical tumor stage (adjusted HR = 24.665; 95% CI 2.601–233.992; p = 0.005) and high ki67 index (adjusted HR = 19.134; 95% CI 1.776–206.098; p = 0.015) were significantly associated with worse DDFS (Table 5). Table 5 Univariate and multivariate analysis for CDR1-AS expression or clinicopathological characteristics and distant disease-free survival (DDFS)

Variable	Categories	Univariate	Multivariate	
HR	95% CI	p	HR	95% CI	p	
Age	 > 50, ≤ 50	0.890	0.199–3.977	0.879	0.291	0.046–1.838	0.189	
Clinical T stage	T4, T2-T3	6.264	1.212–32.385	0.029*	24.665	2.601–233.922	0.005*	
ER status	Positive, negative	0.913	0.204–4.080	0.905	0.438	0.043–4.438	0.485	
PR status	Positive, negative	1.223	0.237–6.304	0.810	1.914	0.177–20.662	0.593	
HER2 status	Positive, negative	2.192	0.490–9.798	0.304	1.661	0.319–8.641	0.546	
Ki67 index	 > 30, ≤ 30	4.116	0.495–34.194	0.190	19.134	1.776–206.098	0.015*	
BMI	 ≥ 24, < 24	1.118	0.250–4.996	0.884	0.656	0.096–4.507	0.668	
CDR1-AS	High, low	0.158	0.019–1.317	0.088	0.078	0.006–0.972	0.047*	
Clinical T stage Clinical tumor stage, ER estrogen receptor, PR progesterone receptor, HER2 human epidermal growth factor receptor 2, BMI body mass index

Discussion

To the best of our knowledge, this study is the first to evaluate the value of CDR1-AS expression for predicting efficacy of neoadjuvant therapy in LABC based on data from prospective clinical trials. We unfolded the prognostic value of CDR1-AS for survival outcomes in patients with LABC for the first time.

pCR is still the main indicator for evaluating the efficacy of neoadjuvant chemotherapy (NAC) and predicting prognosis. Various studies have evaluated the prognostic significance of pCR after NAC. A large meta-analysis of 27895 patients found that achieving pCR following NAC was associated with significantly better event-free survival (EFS) and overall survival (OS), particularly for triple-negative and HER2 + BC [18]. Our multivariate logistic analysis showed that CDR1-AS was an independent predictive factor for pCR in patients with LABC. Patients with low CDR1-AS expression were more likely to achieve pCR. In our clinical study, a neoadjuvant chemotherapy regimen of paclitaxel combined with cisplatin was administered to patients with BC [13]. Currently, no clinical studies have investigated the role of CDR1-AS in predicting the efficacy of NAC in patients with BC. However, some basic studies have suggested that CDR1-AS is indeed related to the efficacy of chemotherapy in cancer cells, especially those treated with cisplatin. Zhao et al. reported that CDR1-AS is highly expressed in cisplatin-resistant cells and that the CDR1-AS/miR-641/HOXA9 axis promotes NSCLC cisplatin resistance by regulating cancer stem cells [19]. Meanwhile, a study by Mao et al. documented that the higher expression of CDR1-AS is an independent prognostic factor in lung adenocarcinoma, and is predictive of resistance to pemetrexed and cisplatin since CDR1-AS could induce the EGFR/PI3K signaling pathway [20]. These studies suggest that CDR1-AS can reduce the sensitivity of tumors to chemotherapy, which may at least partially support our findings.

The results of the subgroup analysis demonstrated that pCR benefits with low CDR1-AS expression were observed across all subgroups, indicating that CDR1-AS was an ideal biomarker and its chemosensitive prediction function was not affected by routine clinicopathological conditions. Particularly, low CDR1-AS expression was related to a higher pCR rate in patients aged ≥ 50 years or with a clinical N1–3 stage, ki67 > 30%, or BMI < 24 sub-populations. The internal mechanism underlying this phenomenon remains unclear and needs to be further elucidated. Future trials should consider CDR1-AS expression as an important factor.

To date, the relationship between CDR1-AS and survival of patients with BC receiving neoadjuvant therapy remains unreported. Our study showed, for the first time, that CDR1-AS expression could be an independent prognostic factor for BC treated with NAC. We found that the expression of CDR1-AS was closely associated with DFS (log-rank p = 0.022) and RFS (log-rank p = 0.012) in patients with BC who had received NAC. After multi-factor adjustment, the DFS, RFS, and DDFS of patients with low CDR1-AS expression were significantly worse than those of patients with high expression (p = 0.041, p = 0.020, and p = 0.047, respectively). However, the study by K. Uhr et al. suggests that the expression of CDR1-AS is not associated with the metastasis-free survival and overall survival of BC patients [21]. The survival outcome discrepancy between our study and K. Uhr’s work [21] may be partially explained by differences in patient selection: 90.6% (96/106) of patients in our study are lymph node-positive, while all patients in K. Uhr’s work are lymph node-negative. Moreover, our patients come from a prospective randomized controlled cohort. The patients in our cohort are LABC patients who had received neoadjuvant therapy. While there are two cohort of patients in K. Uhr’s work, one cohort includes primary BC patients who had not received any systemic (neo)adjuvant therapy, and the other cohort consists of hormone receptor positive metastatic BC patients. The stages and treatments of the patients in the two studies are different. Another reason for the diverse results of the two studies might be the different treatment. Our patient had received systemic (neo)adjuvant therapy while K. Uhr’s cohort had not received any systemic (neo)adjuvant therapy. Furthermore, the patients of both studies were from different regions, which may account for the discrepant result. Despite the shortage of CDR1-AS related clinical data, several basic findings demonstrated that the downregulated expression of CDR1-AS is associated with enhanced malignant biological behavior in tumor cells [7, 8, 22], which is partially consistent with our study. A study by Hanniford et al. showed that the loss of CDR1-AS expression promoted melanoma invasion and metastasis via an IGF2BP3-mediated mechanism [8]. Another work by Lou et al. revealed that CDR1-AS depletion might play a potent role in promoting tumorigenesis by downregulating p53 expression in patients with glioma [7]. Moreover, CDR1-AS knockdown facilitated gastric cancer cell migration and invasion in vitro and in vivo by targeting the miR-876-5p/GNG7 Axis [22]. In summary, our results suggest that CDR1-AS can be used as an effective prognostic marker for survival.

Our study showed that a high pCR rate was achieved in patients with low CDR1-AS expression, and patients with high expression CDR1-AS had better survival. As previously reported, CDR1-AS inhibits tumorigenesis and cancer progression [7, 8]. The nature of CDR1-AS is similar to that of the estrogen receptor, of which the positivity is less sensitive to chemotherapy and is related to better prognosis among patients with BC [4]. Therefore, tumors with higher CDR1-AS expression are well-differentiated, which is related to a lower pCR rate but better prognosis.

The expression pattern of CDR1-AS varies in different tumors. In the case of ovarian and bladder cancers, CDR1-AS expression are found to be reduced, suggesting its role as a suppressor of tumorigenesis [23, 24]. Conversely, in colorectal cancer, the levels of CDR1-AS is elevated, and it appears to act as a facilitator of tumor growth [25]. Our research has also observed that in BC, CDR1-AS expression is lower compared to that in normal tissue. These observations suggest that CDR1-AS may serve dual roles as either a promoter or suppressor of tumor development. Further investigation is warranted to elucidate its complex functions in different cancers.

This study has some limitations. Its sample size was small, and the results require verification in a larger cohort in the future. Our research suggests that patients with low CDR1-AS expression are sensitive to chemotherapy and easily achieve pCR, which implies certain intrinsic regularity and provides guidance for further prospective large-sample clinical studies for validation. The mechanism underlying this phenomenon requires further investigation.

Conclusions

Our research sheds light on the value of CDR1-AS as a potential novel biomarker for predicting pCR and survival benefit in patients with LABC. Our study may help identify specific patient subgroups and guide treatment strategies. However, the role of CDR1-AS in chemoresistance remains unclear.

Abbreviations

NAC Neoadjuvant chemotherapy

BC Breast cancer

LABC Locally advanced breast cancer

pCR Pathological complete response

DFS Disease-free survival

RFS Relapse-free survival

DDFS Distant disease-free survival

circRNA Circular RNA

EFS Event-free survival

OS Overall survival

ER Estrogen receptor

PR Progesterone receptor

IHC Immunohistochemistry

HER2 Human epidermal growth factor receptor 2

ROC Receiver operating characteristic

DCA Decision curve analysis

qRT-PCR Real-time quantitative reverse transcription polymerase chain reaction

Acknowledgements

We would like to thank all the investigators and patients participating in this study.

Author contributions

JS Lu, WJ Yin, LH Zhou and CW Yuan designed and conducted the study. YP Lin, SG Xu, YM Ye, F Yang, and TT Yan collected the clinical data. CW Yuan, J Peng, R Sha and XR Dong carried out RNA extraction and RT-qPCR. CW Yuan and YQ Xu performed data analysis. CW Yuan drafted the manuscript. JS Lu and YH Wang revised the manuscript. All authors have read and approved the final manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by National Natural Science Foundation of China (No. 82203279, 82203093, 82173115 and 82103695), Clinical Research Plan of Shanghai Hospital Development Center (No. SHDC2020CR3003A), Science and Technology Commission of Shanghai Municipality (No. 20DZ2201600), Shanghai Municipal Key Clinical Specialty, Shanghai ‘Rising Stars of Medical Talent’ Youth Development Program for Outstanding Youth Medical Talents (No. 2018-16), Shanghai Rising-Star Program (No. 22QC1400200), Multidisciplinary Cross Research Foundation of Shanghai Jiao Tong University (No. YG2019QNA28), Clinical Research Innovation Nurturing Fund of Renji Hospital and United Imaging (No. 2021RJLY-002), Nurturing Fund of Renji Hospital (No. PYIII20-09, PY2018-III-15 and RJPY-LX-002), and Postdoctoral Fellowship Program of China Postdoctoral Science Foundation (No. GZC20230153).

Availability of data and materials

The datasets reported in the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The research protocols of both clinical trials SHPD001 (NCT02199418) and SHPD002 (NCT02221999) were reviewed and approved by the Independent Ethics Committee of Renji Hospital, School of Medicine, Shanghai Jiaotong University. Written informed consent was obtained from all patients.

Consent for publication

All authors agreed to publish this manuscript.

Competing interests

The authors declare no competing interests.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Chenwei Yuan and Yaqian Xu have contributed equally to this paper.
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