A microRNA-based liquid biopsy signature for the early detection of esophageal squamous cell carcinoma: a retrospective, prospective and multicenter study

Miyoshi, **sei; Zhu, Zhongxu; Luo, Ai**; Toden, Shusuke; Zhou, Xuantong; Izumi, Daisuke; Kanda, Mitsuro; Takayama, Tetsuji; Parker, Iqbal M.; Wang, Minjie; Gao, Feng; Zaidi, Ali H.; Baba, Hideo; Kodera, Yasuhiro; Cui, Yong**; Wang, **n; Liu, Zhihua; Goel, Ajay

doi:10.1186/s12943-022-01507-x

A microRNA-based liquid biopsy signature for the early detection of esophageal squamous cell carcinoma: a retrospective, prospective and multicenter study

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Published: 11 February 2022

Volume 21, article number 44, (2022)
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A microRNA-based liquid biopsy signature for the early detection of esophageal squamous cell carcinoma: a retrospective, prospective and multicenter study

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**sei Miyoshi^1,2,3^na1,
Zhongxu Zhu^4,5^na1,
Ai** Luo⁶^na1,
Shusuke Toden¹^na1,
Xuantong Zhou⁶,
Daisuke Izumi⁷,
Mitsuro Kanda⁸,
Tetsuji Takayama²,
Iqbal M. Parker⁹,
Minjie Wang¹⁰,
Feng Gao¹¹,
Ali H. Zaidi¹²,
Hideo Baba⁷,
Yasuhiro Kodera⁸,
Yong** Cui^13,14,
**n Wang⁴^na1,
Zhihua Liu⁶^na1 &
…
Ajay Goel ORCID: orcid.org/0000-0003-1396-6341^1,15,16^na1

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Abstract

Background

Currently, there is no clinically relevant non-invasive biomarker for early detection of esophageal squamous cell carcinoma (ESCC). Herein, we established and evaluated a circulating microRNA (miRNA)-based signature for the early detection of ESCC using a systematic genome-wide miRNA expression profiling analysis.

Methods

We performed miRNA candidate discovery using three ESCC tissue miRNA datasets (n = 108, 238, and 216) and the candidate miRNAs were confirmed in tissue specimens (n = 64) by qRT-PCR. Using a serum training cohort (n = 408), we conducted multivariate logistic regression analysis to develop an ESCC circulating miRNA signature and the signature was subsequently validated in two independent retrospective and two prospective cohorts.

Results

We identified eighteen initial miRNA candidates from three miRNA expression datasets (n = 108, 238, and 216) and subsequently validated their expression in ESCC tissues. We thereafter confirmed the overexpression of 8 miRNAs (miR-103, miR-106b, miR-151, miR-17, miR-181a, miR-21, miR-25, and miR-93) in serum specimens. Using a serum training cohort, we developed a circulating miRNA signature (AUC:0.83 [95%CI:0.79–0.87]) and the diagnostic performance of the miRNA signature was confirmed in two independent validation cohorts (n = 126, AUC:0.80 [95%CI:0.69–0.91]; and n = 165, AUC:0.89 [95%CI:0.83–0.94]). Finally, we demonstrated the diagnostic performance of the 8-miRNA signature in two prospective cohorts (n = 185, AUC:0.92, [95%CI:0.87–0.96]); and (n = 188, AUC:0.93, [95%CI:0.88–0.97]). Importantly, the 8-miRNA signature was superior to current clinical serological markers in discriminating early stage ESCC patients from healthy controls (p < 0.001).

Conclusions

We have developed a novel and robust circulating miRNA-based signature for early detection of ESCC, which was successfully validated in multiple retrospective and prospective multinational, multicenter cohorts.

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Background

Esophageal cancer is the sixth leading cause of cancer-related deaths, and the eighth most common cancer worldwide, with a higher prevalence in specific geographical locations and certain ethnicities [1, 2]. Esophageal squamous cell carcinoma (ESCC) accounts for almost 80% of all esophageal cancer cases worldwide, with particularly high incidence rates in Eastern Asia and several regions of Africa [3]. The average 5-year survival rate for ESCC varies between 10 and 41% [Full size image

To evaluate the diagnostic potential of the 18-miRNA panel, we employed a two-pronged strategy. First, within each dataset, we performed multivariate logistic regression with 2-fold cross-validations (repeated 100 times) to demonstrate the diagnostic performance of the signature (average AUC = 0.98, 0.99, 0.98, respectively; Fig. 2). Second, we trained a multivariate logistic regression model on the GSE55856 dataset, and then applied the same statistical model to all three datasets in order to further validate and confirm the diagnostic performance of the 18-miRNA signature (AUC = 0.99, 1.00, 0.99, respectively; Fig. S3).

Next, to determine the functional significance of these candidate miRNAs, we constructed a miRNA–mRNA regulatory network based on experimentally validated miRNA–target interactions obtained from the miRTarBase database (V8). In total, we identified 393 genes that were differentially expressed between tumor and normal samples in the TCGA dataset based on the following criteria, |log2 fold-change| > 2 and BH-adjusted p < 0.01, as targets of the 18 miRNAs (Fig. S4A, Table S2). As expected, these miRNA target genes were significantly enriched in cancer-related signaling pathways, such as epithelial-to-mesenchymal transition and angiogenesis pathways (Fig. S4B, Table S3). To ensure that these 18 miRNAs are dysregulated in ESCC, we analyzed a cohort of 32 ESCC and 32 matched adjacent normal tissue specimens to confirm the upregulation of all 18 miRNAs in ESCC (p < 0.05, paired student t-tests; Fig. S5); highlighting their diagnostic significance and biological relevance in esophageal cancer.

Training and validation of an 8-miRNA circulating signature in serum from retrospective cohorts of ESCC patients

Considering that our aim was to develop a non-invasive liquid biopsy assay, we next examined the diagnostic performance of the tissue-based 18-miRNA panel for its translational potential in a serum-based biomarker prioritization cohort (50 ESCC, 50 healthy controls). Among the 18 miRNAs, the expression levels of four miRNAs (miR-182, miR-183, miR-18a and miR-505) were below the detection limit in serum specimens (average PCR cycle threshold > 35; Table S4) [25]. For the remaining 14 miRNAs, eight (miR-103, miR-106b, miR-151, miR-17, miR-181a, miR-21, miR-25 and miR-93) were significantly upregulated in serum from ESCC patients compared to healthy controls (p < 0.05, student t-tests; Fig. S6). From a clinical standpoint, measurement of an upregulated marker in blood is more practical, therefore we focused on 8 upregulated miRNA candidate and interrogated the diagnostic performance of the 8-miRNA panel in training cohort of patients (280 ESCC, 128 healthy controls), which allowed us to construct a multivariate logistic regression model (Table S4). We subsequently derived a risk-scoring formula using logistic regression. For all retrospective serum cohorts, we used this scoring formula and Youden’s index (0.582) derived from the serum training cohort as the cutoff thresholds to dichotomize high- and low-risk groups. Using the risk-scoring formula and the cutoff values, we evaluated the diagnostic performance of this 8-miRNA panel in the training cohort by means of AUC and corresponding 95% confidence intervals, sensitivity, and specificity. Interestingly, for the serum training cohort, this miRNA signature achieved an AUC of 0.83 (95% CI, 0.79–0.87), a sensitivity of 78%, and a specificity of 75% (Fig. 3A and S7A).

To further confirm the diagnostic performance of this 8-miRNA signature, we assessed its performance in two additional independent patient cohorts, where we were able to collect serum specimens – the serum validation cohort 1 (106 ESCC patients and 20 healthy controls) and serum validation cohort 2 (123 ESCC patients and 42 healthy controls). Consistent with the serum training cohort, our circulating miRNA signature achieved a robust performance in both serum validation cohort 1 (Fig. 3B, S7B, AUC = 0.80, 95% CI: 0.69–0.91, sensitivity: 89%, specificity: 60%) and serum validation cohort 2 (Fig. 3C, S7C, S8, Table S5, AUC = 0.89, 95% CI: 0.83–0.94, sensitivity: 87%, specificity: 85%).

Next, using the serum validation cohort 2, we compared the diagnostic performance of our 8-miRNA signature against that of a classic tumor marker in ESCC patients – the squamous cell carcinoma-related antigen (SCC-Ag). While the SCC-Ag levels exhibited modest diagnostic efficiency (Fig. 3C, AUC = 0.72, 95% CI: 0.60–0.84, sensitivity: 0.91, specificity: 0.69), our 8-miRNA panel was significantly superior in distinguishing ESCC patients across all disease stages (Fig. 3C, p = 0.003, DeLong’s test). Furthermore, even when we evaluated specifically in stage I ESCC patients, our circulating miRNA signature maintained its diagnostic performance in discriminating stage I ESCC patients (n = 20) from healthy controls (n = 42; AUC = 0.82, 95% CI:0.70–0.94, sensitivity: 0.76, specificity: 0.91). Likewise, our biomarker panel also maintained its superiority to SCC-Ag in the stage I patients as well (p = 0.025, DeLong’s test; AUC = 0.63, 95% CI: 0.50–0.78, sensitivity: 0.75, specificity: 0.69; Fig. 3D, Table S5), highlighting its potential as a promising early diagnostic assay.

To investigate whether our 8-miRNA panel has a diagnostic specificity for ESCC and not other cancer types, we evaluated the diagnostic performance of our 8-miRNA panel in other major malignancies including colorectal, prostate, lung and breast cancer using public serum miRNA datasets. The scoring formula of the 8-miRNA panel was applied to these datasets and the diagnostic performance of the panel discriminating cancer patients from healthy controls in each cancer types was evaluated. Compared to ESCC, the AUC values of the 8-miRNA panel substantially decreased in other cancer types (combined ESCC validation cohorts VS. other cancer types, all P < 0.05, DeLong’s tests, Fig. S9), suggesting that our 8-miRNA panel is specific to ESCC. Collectively, these data support the diagnostic efficacy of the 8-miRNA signature, as well as its promising potential for the detection of early stage ESCC.

Validation of the diagnostic performance of the circulating miRNA signature in two, independent, prospective cohorts of ESCC patients

To demonstrate the clinical application of our circulating miRNA signature in true clinical settings, we next examined its performance in two, randomized, prospectively enrolled patient cohorts. We performed qRT-PCR assays to assess the expression of the 8-miRNAs signature in 186 serum specimens (Bei**g-1 cohort; 84 ESCC patients and 102 healthy controls) and used this cohort as our training set. We performed multivariate logistic regression analysis and derived a risk-scoring formula: logit(P) = (0.00810 x miR17)–(0.183 x miR21)–(0.974 x miR25) + (0.973 x miR93)–(0.347 x miR103)–(0.298 x miR106b)-(0.194 x miR151) + (0.226 x miR181a)-3.196. Our 8-miRNA signature performed robustly in its ability to distinguish ESCC patients from healthy controls (Fig. 4A, S10A, S11A, AUC = 0.92, 95% CI: 0.87–0.96, sensitivity: 89%, specificity: 84%). Subsequently, we assessed the performance of this miRNA signature in an independent validation cohort (Bei**g-2 cohort; 89 ESCC patients and 99 healthy controls). Once again, our signature robustly distinguished ESCC patients from healthy controls (Fig. 4B, S10B, S11B, S12, AUC = 0.93, 95% CI: 0.88–0.97, sensitivity: 93%, specificity: 89%; Table S6). In both training and validation cohorts, our 8-miRNA signature performed substantially better than individual miRNAs in identifying ESCC patients (S11A and S11B).

In both cohorts, compared to the conventional tumor markers including SCC-Ag, CEA, and CYFRA21-1, our 8-miRNA panel consistently demonstrated superior diagnostic performance for the identification of ESCC patients across all stages (Table S6, Fig. 4A, B, all p < 0.01, DeLong’s tests). Notably, when we focused on stage I ESCC patients, our 8-miRNA signature remarkably discriminated stage I ESCC patients from healthy controls in both Bei**g-1 cohort (AUC = 0.97, 95% CI:0.93–1.00, sensitivity: 0.92, specificity: 0.92) and Bei**g-2 cohorts (AUC = 0.89, 95% CI: 0.77–1.00, sensitivity: 92%, specificity: 90%); and in each instance its performance was substantially superior to that of SCC-Ag and CEA, which are routinely analyzed in clinical settings (Table S7, Fig. 4C and D, all p < 0.05, DeLong’s tests). We performed univariate and multivariate analyses to confirm that our circulating miRNA signature was the only significant predictor for detecting ESCC patients from all stages (Table S8), as well as stage I patients specifically (Table S9).

The 8-miRNA signature robustly identifies patients with high-risk premalignant lesions and is cost-effective vs. currently used diagnostic approaches in the clinic

Next, we investigated the earliest possible lesions that could be detected with our non-invasive circulating miRNA panel. Since the diagnostic risk scores were significantly elevated in stage I–IV ESCC patients (all p < 0.001, one-sided Student’s t-tests), we examined the diagnostic performance of the 8-miRNA panel for identifying patients with high-grade intraepithelial neoplasia. Intriguingly, the panel was able to identify patients with high-grade intraepithelial neoplasia (n = 13, p < 0.01, one-sided Student’s t-test; Fig. 5). However, the risk scores did not change significantly in patients with low-grade intraepithelial neoplasia (n = 8) or those with esophagitis (n = 6) compared to healthy controls (Fig. 5). These results suggest a potential use of our circulating miRNA signature for early detection of high-risk premalignant lesions.

To determine whether screening using our miRNA signature would be cost effective, we performed cost effective analysis (see Supplementary Material for details). We estimated mass screening using our circulating miRNA signature to be cost-effective relative to current practice [ICER = CNY 15,800.4/QALY] (Tables S10, S11). In summary, our circulating miRNA signature demonstrated promising diagnostic performance in our multinational, multicenter cohort study, and is likely to provide a cost-efficient, highly robust option for non-invasive early detection of ESCC.

Discussion

ESCC is one of the most aggressive cancers and its low patient survival rate is primarily due to delayed diagnosis [26]. Therefore, early detection of ESCC provides opportunities to implement effective treatment strategies and timely interventions to improve patients’ overall outcomes. However, there is currently no clinically viable molecular marker for non-invasive diagnosis of ESCC. In this study, we performed a comprehensive bioinformatics analysis to identify candidate miRNAs from three in silico datasets and subsequently developed a panel of 8 circulating miRNAs for non-invasive ESCC detection. We demonstrated the diagnostic performance of the miRNA diagnostic panel in several large, independent, retro-prospective, multinational, multicenter cohorts.

Both genetic and epigenetic changes are recognized as the key contributors in cancer development. miRNAs have been recognized as promising non-invasive biomarker candidates, primarily due to their structural stability and abundance in circulation [27]. Accordingly, a plethora of studies has examined the diagnostic potential of circulating miRNAs in various cancers, including ESCC [11, 28]. While epigenetic alterations occur more frequently at an early stages of cancer development, mutations in p53, the most frequently occurring mutations in ESCC, have been shown to modulate the expression levels of miRNAs [29].

In ESCC, the expression of several circulating miRNAs has been evaluated individually for ESCC diagnosis and several studies have attempted to combine multiple miRNAs to establish a miRNA-based ESCC diagnostic panel [11, 30, 31]. However, the diagnostic potential of individual circulating miRNA markers was limited, and the panels derived for the detection of ESCC were constructed with poor or biased candidate selection criteria and lacked validation in multiple cohorts. Although these studies highlight the clinical usefulness of circulating miRNAs, the above limitations result in poor data interpretation. Furthermore, although ethnicity and geographical distribution play a major role in ESCC incidence [3], previous studies did not account for such variations when assessing the diagnostic performance of their miRNA markers. In this study, we successfully established systematic, comprehensive, and reliable biomarker discovery approach, using numerous global, multicenter, and retro-prospective cohorts of more than 1800 clinical specimens. To our knowledge, we tested our panel using the largest and most ethnically and geographically diverse ESCC sample collection to date. In addition, we showed that the miRNA panel had a significantly superior detection capability compared to conventional clinical serological markers, including SCC-Ag, the most commonly used serum diagnostic marker for ESCC [32]. We also showed using multiple cancer datasets that our miRNA panel was specific to ESCC diagnosis and not other cancer types. Furthermore, the strongest point of our study is that we expanded evaluation of our miRNA panel to prospectively collected samples to accurately assess its diagnostic performance. Although our 8-miRNA signature demonstrated effectiveness regardless of race (i.e., in two Asian and one African cohort) in our retrospective validation, it is important note that the diagnostic classifiers were developed using primarily Asian cohorts. Therefore, future studies are needed to optimize performance of the risk-scoring model in additional prospective serum cohorts and test the diagnostic performance of the classifiers in cohorts comprised of non-Asian races. Another potential limitation of our study is that we prioritized miRNA biomarkers that were overexpressed in ESCC tissues, with the hypothesis that such miRNAs are the most likely to be released into systemic circulation. However, recent studies have indicated that some miRNAs that do not accumulate in tissues may still be excreted in extracellular-vesicles such as exosomes [33, 34]. In addition, although our diagnostic miRNA panel was robust in identified ESCC patients, we acknowledge that a portion of patients had false positive outcomes. Lastly, given that the primary focus of our present study was development of a diagnostic assay for ESCC, we are unable to determine whether these markers could also predict response to treatment in ESCC patients as well – an important consideration that will pursue in subsequent studies. Based on the cancer screening biomarker pipeline [35], we plan to perform a retrospective performance study [36] to evaluate the diagnostic performance of the miRNA signature.

In conclusion, we used a comprehensive biomarker discovery process with three large independent public datasets, one tissue cohort, and four retrospective and two prospective large independent serum cohorts to develop and successfully validate a novel and robust miRNA-based signature for the early detection of ESCC. While additional validation studies are required to comprehensively evaluate the performance of our classifiers, our miRNA signature has the potential to transform noninvasive diagnosis for ESCC patients in the future.

Availability of data and materials

All data derived from public database are available from these sites.

TCGA Research Network: http://cancergenome.nih.gov/ (ESCC dataset).

Gene Expression Omnibus https://www.ncbi.nlm.nih.gov/geo/ (GSE55856, and GSE43732).

All other data are available on reasonable request from the corresponding authors.

Abbreviations

ESCC:: Esophageal squamous cell carcinoma
miRNA:: MicroRNA
TCGA:: The Cancer Genome Atlas
AUC:: Area under the curve
CI:: Confidence interval
SCC:: Squamous cell carcinoma
GEO:: Gene expression omnibus
BC:: Breast cancer
CRC:: Colorectal cancer
PC:: Prostate cancer
LC:: Lung cancer
ROC:: Receive operator characteristic curve

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Acknowledgements

We would like to thank Dr. Rebecca Fitzgerald for critical reading and for providing valuable insights that allowed us to significantly improve the quality of this article.

Funding

The present work was supported by CA72851, CA181572, CA184792, CA187956, and CA202797 grants from the National Cancer Institute, National Institutes of Health, RP140784 from the Cancer Prevention Research Institute of Texas, grants from the Sammons Cancer Center and Baylor Foundation, as well as funds from the Baylor Scott & White Research Institute, Dallas, TX, USA awarded to AG; by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. 11103718, 11103619, 11103921, R4017–18, C4041-17GF, AoE/M-401/20), a grant from Guangdong Basic and Applied Basic Research Foundation (Project No. 2019B030302012), and a grant from National Natural Science Foundation of China (Project No. 81802384) awarded to ** Luo, Shusuke Toden, ** Luo, Xuantong Zhou & Zhihua Liu

Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan

Daisuke Izumi & Hideo Baba

Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan

Mitsuro Kanda & Yasuhiro Kodera

Division of Medical Biochemistry and Structural Biology, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa

Iqbal M. Parker

Department of Clinical Laboratory, Chinese Academy of Medical Sciences and Peking Union Medical College, Bei**g, China

Minjie Wang

The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China

Feng Gao

Esophageal and Lung Institute, Allegheny Health Network, Pittsburgh, PA, USA

Ali H. Zaidi

Cancer Institute, Shenzhen Bay Laboratory, Shenzhen, China

Yong** Cui

Cancer Institute, Peking University Shenzhen Hospital, Shenzhen Peking University-Hong Kong University of Science and technology (PKU-HKUST) Medical Center, Shenzhen, China

Yong** Cui

Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA

Ajay Goel

City of Hope Comprehensive Cancer Center, Duarte, CA, USA

Ajay Goel

Authors

**sei Miyoshi
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Zhongxu Zhu
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Ai** Luo
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Shusuke Toden
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Xuantong Zhou
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Daisuke Izumi
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Mitsuro Kanda
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Tetsuji Takayama
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Iqbal M. Parker
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Minjie Wang
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Feng Gao
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Ali H. Zaidi
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Hideo Baba
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Yasuhiro Kodera
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Yong** Cui
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**n Wang
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Zhihua Liu
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Ajay Goel
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Contributions

Concept and design: MJ, ZZ, ST, YC, ZL, XW and AG. Acquisition, analysis, or interpretation of data: JM, ZZ, AL, FG, and XW. Drafting of the manuscript: JM, ZZ, AL, ST, XW, ZL and AG. Critical revision of the manuscript for important intellectual content: JM, ZZ, AL, ST, XW, ZL and AG. Statistical analysis: JM, ZZ, JT and XW. Administrative, technical, or material support: JM, ZZ, AL, ST, DI, MK, AZ, IMP, MW, HB, YK, XW, YC, ZL and AG. Supervision: ZL, XW and AG. The author(s) read and approved the final manuscript.

Author’s information

Not applicable.

Corresponding authors

Correspondence to **n Wang, Zhihua Liu or Ajay Goel.

Ethics declarations

Ethics approval and consent to participate

All study-related procedures were performed as per the Declarations of Helsinki, wherein a written informed consent was obtained from each patient, and the institutional review boards of all participating institutions involved approved the study.

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Not applicable. The manuscript does not contain any individual personal data.

Competing interests

The authors have no competing interests to disclose.

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Supplementary Information

Additional file 1: Supplementary Figure 1.

Study design for the identification and validation of the circulating miRNA panel for ESCC detection. Supplementary Figure 2. 18-miRNAs can distinguish between tumor and normal tissues. Supplementary Figure 3. In silico validation for 18-miRNA panel and Silhouette analysis. Supplemental Figure 4. miRNA regulatory network analysis and functional analysis of miRNA target genes. Supplemental Figure 5. Tissue validation for initial miRNA candidates. Supplemental Figure 6. Selection of circulating miRNAs in the serum biomarker prioritization cohort. Supplementary Figure 7. The robustness of the miRNA-classifier in training and validation cohorts. Supplemental Figure 8. Confusion matrices analysis for validation cohort 2. Supplemental Figure 9. Specificity analysis for the 8-miRNA panel on multiple cancer types. Supplemental Figure 10. The robustness of the miRNA-classifier in the prospectively collected cohorts. Supplemental Figure 11. Specificity analysis for the 8-miRNA panel and individual miRNAs. Supplemental Figure 12. Confusion matrices analysis for the Bei**g-2 prospective cohort. Supplemental Table 1. Characteristics of in silico discovery sets. Supplemental Table 2. miRNA–mRNA interactions in the regulatory network. Supplemental Table 3. Functional analysis of miRNA target genes identified 31 significantly enriched signaling pathways and Hallmark gene sets (BH-adjusted p-value < 0.05). Supplemental Table 4. miRNA panel selection and logistic regression model in serum biomarker prioritization and training phases. Supplemental Table 5. Prediction of serum 8-miR panel and serum SCC-Ag for the differential diagnosis of ESCC from healthy participants in serum training and serum validation cohorts. Supplemental Table 6. Comparison of the performance of the circulating miRNA signature against SCC-Ag, CEA, CA72–4, and CYFRA21-1 for non-invasive detection of ESCC across all stages in randomized prospective serum cohorts. Supplemental Table 7. Benchmark the performance of the circulating miRNA signature against SCC-Ag and CEA for non-invasive detection of stage I ESCC in randomized prospective serum cohorts. Supplemental Table 8. Univariate and multivariate analyses of the circulating miRNA signature with SCC-Ag, CEA, CA72–4, and CYFRA21-1 for non-invasive detection of ESCC across all stages in randomized prospective serum cohorts. Supplemental Table 9. Univariate and multivariate analyses of the circulating miRNA signature with SCC-Ag and CEA for non-invasive detection of stage I ESCC in randomized prospective serum cohorts. Supplemental Table 10. Results of cost-effectiveness analysis for non-invasive screening for Chinese men in China (> 40 years old). Supplemental Table 11. Base-case values in cost-effectiveness modeling.

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Miyoshi, J., Zhu, Z., Luo, A. et al. A microRNA-based liquid biopsy signature for the early detection of esophageal squamous cell carcinoma: a retrospective, prospective and multicenter study. Mol Cancer 21, 44 (2022). https://doi.org/10.1186/s12943-022-01507-x

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Received: 13 October 2021
Accepted: 12 January 2022
Published: 11 February 2022
DOI: https://doi.org/10.1186/s12943-022-01507-x

A microRNA-based liquid biopsy signature for the early detection of esophageal squamous cell carcinoma: a retrospective, prospective and multicenter study