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Real-life disease monitoring in follicular lymphoma patients using liquid biopsy ultra-deep sequencing and PET/CT

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Abstract

In the present study, we screened 84 Follicular Lymphoma patients for somatic mutations suitable as liquid biopsy MRD biomarkers using a targeted next-generation sequencing (NGS) panel. We found trackable mutations in 95% of the lymph node samples and 80% of the liquid biopsy baseline samples. Then, we used an ultra-deep sequencing approach with 2 · 10−4 sensitivity (LiqBio-MRD) to track those mutations on 151 follow-up liquid biopsy samples from 54 treated patients. Positive LiqBio-MRD at first-line therapy correlated with a higher risk of progression both at the interim evaluation (HRINT 11.0, 95% CI 2.10–57.7, p = 0.005) and at the end of treatment (HREOT, HR 19.1, 95% CI 4.10–89.4, p < 0.001). Similar results were observed by PET/CT Deauville score, with a median PFS of 19 months vs. NR (p < 0.001) at the interim and 13 months vs. NR (p < 0.001) at EOT. LiqBio-MRD and PET/CT combined identified the patients that progressed in less than two years with 88% sensitivity and 100% specificity. Our results demonstrate that LiqBio-MRD is a robust and non-invasive approach, complementary to metabolic imaging, for identifying FL patients at high risk of failure during the treatment and should be considered in future response-adapted clinical trials.

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Fig. 1: Baseline genotyping and potential of the liquid biopsy MRD test (LiqBio-MRD) to monitor disease progression.
Fig. 2: Clinical impact of early monitoring by LiqBio-MRD: (left) Swimmer plot of the different follow-up time points screened for all patients under first-line treatment included in the survival analysis.
Fig. 3: Interim monitoring by PET/CT predicts progression in first-line treated patients.
Fig. 4: Clinical Impact of the LiqBio-MRD and PET/CT combination in first-line therapy.
Fig. 5: Examples of the disease dynamics monitored by LiqBio-MRD.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This study has been funded by Instituto de Salud Carlos III (ISCIII) and co-funded by the European Union through the projects PI21/00314, PI19/01430, PI19/01518 and PI18/00295, PTQ2020-011372, CP19/00140, CP22/00082, Doctorado industrial CAM IND2020/TIC-17402 and CRIS cancer foundation.

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Author notes

  1. These authors contributed equally: Ana Jiménez-Ubieto, María Poza, Joaquín Martínez-López, Santiago Barrio.

Authors and Affiliations

  1. Department of Hematology, Hospital Universitario 12 de Octubre, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), CNIO, CIBERONC, Madrid, Spain

    Ana Jiménez-Ubieto, María Poza, Yanira Ruiz-Heredia, Juan Manuel Rosa-Rosa, Antonia Rodriguez, Ricardo Sanchez, Laura Rufian, Alexandra Juárez, Margarita Rodriguez, María Calbacho, Tycho Baumann, Inmaculada Rapado, Miguel Gallardo, Rosa Ayala, Joaquín Martínez-López & Santiago Barrio

  2. Altum sequencing Co., Madrid, Spain

    Alejandro Martin-Muñoz, Yanira Ruiz-Heredia, Sara Dorado, Jaime Carrillo, Ricardo Sanchez, Laura Rufian, Alexandra Juárez, Margarita Rodriguez & Santiago Barrio

  3. Computational Science Department, Carlos III University, Madrid, Spain

    Sara Dorado & Paula de Toledo

  4. Hospital General Universitario de Toledo, Toledo, Spain

    Gloria Figaredo, Laura Parrilla Navamuel, Manuela Mollejo & Luis-Felipe Casado

  5. Hospital Universitario 12 de Octubre, Departamento de Anatomía Patológica, Madrid, Spain

    Carmen Barcena

  6. Hosea Precision Medical Technology Co., Ltd., Weihai, Shangdong, China

    Chongwu Wang

  7. Clínica Universitaria de Navarra, Madrid, Spain

    Carlos Grande

  8. H12O-CNIO Haematological Malignancies Clinical Research Unit, CNIO, Madrid, Spain

    Miguel Gallardo

  9. Hospital Universitario 12 de Octubre, Departamento de Medicina Nuclear, Madrid, Spain

    Pilar Sarandeses

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  1. Ana Jiménez-Ubieto
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  2. María Poza
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Contributions

AJU, MP, IR, MG, RA, JML, and SB designed the research. JC, RS, LR, AJ, and MR performed the experiments. AM, YR, SD and JMR, CW, PT and SB defined the bioinformatic pipeline and performed sequencing data analysis. AJU, MP, GF, AR, CB, LPN, CG, MM, LFC, MC, TB, MG, PS and RS provided patient samples and clinical data. All authors analyzed and interpreted the data. AJU, MP, AM and SB wrote the manuscript which was approved by all authors.

Corresponding authors

Correspondence to Ana Jiménez-Ubieto or Santiago Barrio.

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Competing interests

RA, JML, and SB are equity shareholders of Altum Sequencing Co. LLFC received honoraria and received research funding from Roche, Novartis, Astra Zeneca, Janssen, B.M.S., Pfizer and Incyte. The remaining authors declare no competing financial interests.

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Jiménez-Ubieto, A., Poza, M., Martin-Muñoz, A. et al. Real-life disease monitoring in follicular lymphoma patients using liquid biopsy ultra-deep sequencing and PET/CT. Leukemia 37, 659–669 (2023). https://doi.org/10.1038/s41375-022-01803-x

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