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Microsatellite instability detection in breast cancer using drop-off droplet digital PCR

Oncogene volume 41, pages 5289–5297 (2022)Cite this article

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Abstract

The use of conventional methods (immunohistochemistry, pentaplex PCR) for detecting microsatellite instability (MSI), a predictive biomarker of immunotherapy efficacy, is debated for cancers with low MSI prevalence, such as breast cancer (BC). We developed two multiplex drop-off droplet digital PCR (ddPCR) assays targeting four microsatellites, initially identified from public BC whole-genome sequencing dataset. Performances of the assays were investigated and 352 tumor DNA and 28 circulating cell-free DNA from BC patients, with unknown MSI status were blindly screened. Cross-validation of ddPCR MSI status with other MSI detection methods was performed. We then monitored circulating tumor DNA (ctDNA) dynamics before and during pembrolizumab immunotherapy in one patient with MSI-high (MSI-H) metastatic BC. The assays showed high analytical specificity and sensitivity (limit of detection = 0.16%). Among N = 380 samples, seven (1.8%) were found as MSI-H by ddPCR with six of them confirmed by next-generation sequencing (NGS). Specificity was 100% in N = 133 microsatellite stable BC submitted to NGS. In the patient with MSI-H metastatic BC, ctDNA monitoring revealed an early decrease of microsatellite mutant allelic frequencies during immunotherapy. These results demonstrated MSI detection by ddPCR, a non-invasive, fast and cost-effective approach, allowing for large pre-screening of BC patients who may benefit from immunotherapy.

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Fig. 1: Microsatellite instability detection by drop-off ddPCR assays.
Fig. 2: MSI detection in 3 breast tumors previously known as MSI-H based on NGS.
Fig. 3: Characterization of MSI status by IHC, pentaplex PCR and NGS in the 6 breast tumors retrieved as MSI-H by drop-off ddPCR assays in the blind analysis.
Fig. 4: 2D scatter plots of MSI detection in cfDNA by multiplex M1&M2 and M3&M4 drop-off ddPCR assays.
Fig. 5: Dynamic monitoring of MSI status in metastatic BC cfDNA (P#29) before and after treatment.
Fig. 6: Workflow of the study and patient characteristics.

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Data availability

The human sequence data generated in this study are not publicly available due to patient privacy. Other data generated in this study are available within the article and its supplementary data files.

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Acknowledgements

We thank Laetitia Fuhrmann and the Biological Resource Center (CRB) for providing clinical samples, Frederic Maraone from the Pharmacogenomic service for technical support, Maya Nourieh and Hrant Ghazelian for providing IHC images, Benjamin Renouf and Corinne Ajrizov for retrieving clinical data and Alexandre Houy for providing WES analysis results.

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  1. These authors contributed equally: Shufang Renault, François-Clément Bidard.

Authors and Affiliations

  1. Circulating Tumor Biomarkers Laboratory, Inserm CIC-BT 1428, Department of translational research, Institut Curie, Paris, France

    Khadidja Zeyneb Klouch, Luc Cabel, Amanda Bortolini Silveira, Caroline Hego, Aurore Rampanou, Charlotte Proudhon, Marc Michel, Jean-Yves Pierga, Shufang Renault & François-Clément Bidard

  2. Inserm U830, DNA Repair and Uveal Melanoma (D.R.U.M.) team, Institut Curie, PSL Research University, Paris, France

    Marc-Henri Stern & Tatiana Popova

  3. Department of Diagnostic and Theranostic Medicine, Institut Curie, PSL Research University, Paris, France

    Olfa Trabelsi-Grati, Guillaume Bataillon, Sarah Nasr, Victor Renault, Julien Masliah Planchon, Anne Vincent-Salomon & Ivan Bieche

  4. Department of Medical Oncology, Institut Curie, Paris and Saint Cloud, France

    Nicolas Kiavue, Luc Cabel, Jean-Yves Pierga & François-Clément Bidard

  5. Université de Paris, Paris, France

    Luc Cabel & Jean-Yves Pierga

  6. Inserm U934, CNRS UMR3215, Paris, France

    Charlotte Proudhon & Marc Michel

  7. UVSQ, Paris-Saclay University, Saint Cloud, Paris, France

    François-Clément Bidard

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Contributions

KZK, FCB, SR, and MHS designed the study. KZK, CH, AR, and ABS performed experiments. KZK, FCB, SR, and MHS analyzed data. OTG, IB, FCB, NK, LC, CP, JYP, and AVS contributed with identification of clinical samples. TP performed in silico microsatellite identification. MM performed combinatorial analysis. OTG, JMP and VR performed NGS analysis. GB and SN performed IHC analysis and provided with IHC images. KZK, SR, and FCB wrote the manuscript.

Corresponding authors

Correspondence to Shufang Renault or François-Clément Bidard.

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Competing interests

This work was supported by the Ligue Nationale Contre le Cancer (LNCC, N/Ref: RS21/75-47), Servier (Ref: CT0079257), and the Innovative Medicines Initiative Joint Undertaking under grant agreement n° 115749 (Cancer-ID). AB Silveira, FC Bidard, C Proudhon, and MH Stern are co-inventors of patent PCT/EP 2018/068760, WO2019011971. A patent application on this work where FC Bidard, KZ Klouch, S Renault, AB Silveira, MH Stern, C Proudhon are co-inventors has been filed (24/03/2022, EP22305360). No potential conflicts of interest were disclosed by the other authors.

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Klouch, K.Z., Stern, MH., Trabelsi-Grati, O. et al. Microsatellite instability detection in breast cancer using drop-off droplet digital PCR. Oncogene 41, 5289–5297 (2022). https://doi.org/10.1038/s41388-022-02504-6

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