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Evaluation of EpCAM-specific exosomal lncRNAs as potential diagnostic biomarkers for lung cancer using droplet digital PCR


Accumulating evidence demonstrated that long non-coding RNAs (lncRNAs) derived from exosomes had the potential to be diagnostic markers for lung cancer. However, the diagnostic value of lncRNAs from epithelial cell adhesion molecule (EpCAM)–positive exosomes remains unclear. In the study, serum EpCAM-positive exosomes were isolated with magnetic beads, and their role in lung cancer was investigated in vitro and in vivo. The copy numbers of lncRNAs RP11-77G23.5 and PHEX-AS1 in EpCAM-specific exosomes were quantified by droplet digital PCR (ddPCR). The diagnostic value of RP11-77G23.5 and PHEX-AS1 was tested in the training cohort and verified in the validation cohort. We found that EpCAM-specific exosomes could promote lung cancer development in vitro and in vivo. RP11-77G23.5 and PHEX-AS1 were significantly elevated in EpCAM-specific exosomes from lung cancer patients and could distinguish malignant from benign lung tumors. The amounts of RP11-77G23.5 were statistically higher in the subtype of lung adenocarcinoma (LUAC) than that of lung squamous cell carcinoma (LUSC), showing its capability to subtype LUAC and LUSC, while PHEX-AS1 exhibited distinct expression signatures between lower and higher tumor stages, and without and with distant metastasis, indicating its association with lung cancer progression. In conclusion, the EpCAM-specific exosomal lncRNAs RP11-77G23.5 and PHEX-AS1 may be promising diagnostic biomarkers for lung cancer.

Key messages

  • Serum EpCAM-positive exosomes promote lung cancer development in vitro and in vivo.

  • Two EpCAM-specific exosomal lncRNAs can be simultaneously detected by RT-ddPCR.

  • EpCAM-specific exosomal RP11-77G23.5 has the potential to subtype LUAC and LUSC.

  • EpCAM-specific exosomal PHEX-AS1 is associated with lung cancer progression.

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Data availability

All data generated in this study are included in this published article and its supplementary information files.

Code availability

Not applicable.


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We thank Prof. Junming Guo for providing us with the ddPCR instruments.


The study was partially supported by a grant from the National Natural Science Foundation of China (81902146), the Natural Science Foundation of Zhejiang Province (LQ18H200001), the Program of “Xinmiao” (Potential) Talents in Zhejiang Province (2020R405041, 2021R405044), the Research Project in Ningbo University (JYXMXZD2021031, XYL20028), the Research Project of Education Science in Ningbo City (2020YGH007) and the K.C.Wong Magna Fund in Ningbo University.

Author information




Conception and design: X. Meng.

Development of methodology: X. Shen, Y. Yang, Y. Chen, C. Lou, Y. Huang, D. Tian, Y. Shen. Acquisition of data (acquired and managed patients, provided facilities, etc.): C. Zhou, X. Zhao, N. Li. Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): X. Shen, Y. Yang, Y. Chen. Writing, review, and/or revision of the manuscript: X. Shen, Y. Yang, Y. Chen, X. Meng. Study supervision: X. Meng.

Corresponding author

Correspondence to Xiaodan Meng.

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Ethics approval and consent to participate

All animal experiments were performed in accordance with currently prescribed guidelines and followed a protocol approved by the Medical School of Ningbo University. This study was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all patients, and the study was approved by the ethics committee (the Clinical Research Ethics Committee of Medical School of Ningbo University).

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All the authors have contributed to the work sufficiently to be named as authors and revised the manuscript with the agreement to the submission.

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The authors declare no competing interests.

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Shen, X., Yang, Y., Chen, Y. et al. Evaluation of EpCAM-specific exosomal lncRNAs as potential diagnostic biomarkers for lung cancer using droplet digital PCR. J Mol Med (2021).

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  • EpCAM-specific exosomes
  • Lung cancer
  • Diagnosis
  • Lung adenocarcinoma
  • Squamous cell lung cancer
  • Digital polymerase chain reaction