Integrated Cf-miRNA and Exosomal miRNA Signature for Early Detection of Esophageal Squamous Cell Carcinoma

Официальное название

SYNERGY Study: Early Detection Through Integrated Evaluation of Cell-Free and Exosomal microRNAs for Biomarker-Guided Screening of Esophageal Squamous Cell Carcinoma

Обзор

Esophageal squamous cell carcinoma (ESCC) remains a highly lethal cancer worldwide, largely due to late diagnosis. Current screening methods such as upper endoscopy are invasive, operator-dependent, and limited in their ability to detect early-stage lesions. To address this clinical need, the SYNERGY study seeks to develop a non-invasive, blood-based biomarker assay that integrates cell-free microRNAs (cf-miRNAs) and exosomal microRNAs (exo-miRNAs) to detect ESCC at an early and potentially curable stage. This multicenter translational study includes discovery, training, and validation phases using preoperative plasma or serum samples. By combining the tumor specificity of exosomal miRNAs with the systemic sensitivity of cf-miRNAs, SYNERGY aims to construct a robust diagnostic model with high sensitivity and specificity for early ESCC detection.

Подробное описание

Esophageal cancer is the 11th most common cancer globally and the 7th leading cause of cancer-related death, with an estimated 511,000 new cases and 445,000 deaths annually. ESCC accounts for the majority of cases worldwide. Despite advances in endoscopy and therapy, outcomes for advanced ESCC remain poor, highlighting the pressing need for sensitive, minimally invasive early detection strategies.

Exosomal miRNAs (exo-miRNAs) are selectively released by tumor cells and remain stable in circulation, enabling reliable detection of tumor-specific signals. Cell-free miRNAs (cf-miRNAs) circulate broadly and can reflect overall tumor burden, metastatic spread, and microenvironmental changes.

Previous ESCC biomarker studies were limited by small validation cohorts and reliance on tissue-based public datasets that do not fully capture circulating biomarker patterns. The SYNERGY study addresses these limitations through comprehensive discovery analysis and multi-cohort blood-based validation.

Вмешательства

• Диагностический тест Small RNA sequencing of exo- and cf-miRNAs
  Identification of differentially expressed cf-miRNAs
• Диагностический тест RT-qPCR quantification of cf- and exo-miRNAs (SYNERGY assay)
  RT-qPCR quantification of cf- and exo-miRNAs, and construction of machine learning classifier
• Диагностический тест PCR-based validation (SYNERGY assay)
  PCR-based validation of the SYNERGY miRNA panel

Первичные конечные точки

• Sensitivity [Срок оценки: At study completion, an average of one year]

Вторичные конечные точки (2)

• AUC [Срок оценки: At Study completion, an average of one year]
• Specificity [Срок оценки: Time Frame: At study completion, , an average of one year]

Критерии участия

Критерии включения

• Adults age 18 to 90 years
• Histologically confirmed esophageal squamous cell carcinoma
• No prior systemic therapy before sample collection
• For control groups: absence of malignant disease

Критерии исключения

• Lack of informed consent
• Inadequate sample volume or RNA quality
• Prior cancer within 5 years (except localized cancers)
• Active systemic inflammation that may alter circulating RNA profiles

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Модель наблюдения

Случай-контроль

Центры проведения

США · 1 центр

• City of Hope Medical Center — Monrovia

Публикации

• Mao Y, Fu Z, Zhang Y, Dong L, Zhang Y, Zhang Q, Li X, Wang C. A six-microRNA risk score model predicts prognosis in esophageal squamous cell carcinoma. J Cell Physiol. 2019 May;234(5):6810-6819. doi: 10.1002/jcp.27429. Epub 2018 Nov 1. PMID 30387125
• Li T, Sun G, Ye H, Song C, Shen Y, Cheng Y, Zou Y, Fang Z, Shi J, Wang K, Dai L, Wang P. ESCCPred: a machine learning model for diagnostic prediction of early esophageal squamous cell carcinoma using autoantibody profiles. Br J Cancer. 2024 Sep;131(5):883-894. doi: 10.1038/s41416-024-02781-w. Epub 2024 Jul 2. PMID 38956246
• Li K, Lin Y, Zhou Y, Xiong X, Wang L, Li J, Zhou F, Guo Y, Chen S, Chen Y, Tang H, Qiu X, Cai S, Zhang D, Bremer E, Jim Yeung SC, Zhang H. Salivary Extracellular MicroRNAs for Early Detection and Prognostication of Esophageal Cancer: A Clinical Study. Gastroenterology. 2023 Oct;165(4):932-945.e9. doi: 10.1053/j.gastro.2023.06.021. Epub 2023 Jul 1. PMID 37399999
• Miyoshi J, Zhu Z, Luo A, Toden S, Zhou X, Izumi D, Kanda M, Takayama T, Parker IM, Wang M, Gao F, Zaidi AH, Baba H, Kodera Y, Cui Y, Wang X, Liu Z, Goel A. A microRNA-based liquid biopsy signature for the early detection of esophageal squamous cell carcinoma: a retrospective, prospective and multicenter study. Mol Cancer. 2022 Feb 11;21(1):44. doi: 10.1186/s12943-022-01507-x. PMID 35148754
• Chen J, Zheng Y, Wang Z, Gao Q, Hao K, Chen X, Ke N, Lv X, Weng J, Zhong Y, Huang Z, Fu M, Zhao L, Lin F, Mi H, Tang H, Yu C, Huang Y. Development a glycosylated extracellular vesicle-derived miRNA Signature for early detection of esophageal squamous cell carcinoma. BMC Med. 2025 Jan 23;23(1):39. doi: 10.1186/s12916-025-03871-z. PMID 39849483
• Codipilly DC, Wang KK. Squamous Cell Carcinoma of the Esophagus. Gastroenterol Clin North Am. 2022 Sep;51(3):457-484. doi: 10.1016/j.gtc.2022.06.005. Epub 2022 Aug 29. PMID 36153105
• Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011 Mar-Apr;61(2):69-90. doi: 10.3322/caac.20107. Epub 2011 Feb 4. PMID 21296855
• Codipilly DC, Qin Y, Dawsey SM, Kisiel J, Topazian M, Ahlquist D, Iyer PG. Screening for esophageal squamous cell carcinoma: recent advances. Gastrointest Endosc. 2018 Sep;88(3):413-426. doi: 10.1016/j.gie.2018.04.2352. Epub 2018 Apr 27. PMID 29709526

Идентификаторы

NCT: NCT07266363 · 23228/SYNERGY

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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