Tumour-informed liquid biopsies to monitor advanced melanoma patients under immune checkpoint inhibition.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
09 Oct 2024
09 Oct 2024
Historique:
received:
23
11
2023
accepted:
20
09
2024
medline:
10
10
2024
pubmed:
10
10
2024
entrez:
9
10
2024
Statut:
epublish
Résumé
Immune checkpoint inhibitors (ICI) have significantly improved overall survival in melanoma patients. However, 60% experience severe adverse events and early response markers are lacking. Circulating tumour DNA (ctDNA) is a promising biomarker for treatment-response and recurrence detection. The prospective PET/LIT study included 104 patients with palliative combined or adjuvant ICI. Tumour-informed sequencing panels to monitor 30 patient-specific variants were designed and 321 liquid biopsies of 87 patients sequenced. Mean sequencing depth after deduplication using UMIs was 6000x and the error rate of UMI-corrected reads was 2.47×10
Identifiants
pubmed: 39384805
doi: 10.1038/s41467-024-52923-0
pii: 10.1038/s41467-024-52923-0
doi:
Substances chimiques
Immune Checkpoint Inhibitors
0
Circulating Tumor DNA
0
Biomarkers, Tumor
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
8750Informations de copyright
© 2024. The Author(s).
Références
Wolchok, J. D. et al. Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N. Engl. J. Med. 377, 1345–1356 (2017).
pubmed: 28889792
pmcid: 5706778
doi: 10.1056/NEJMoa1709684
Robert, C. et al. Nivolumab in previously untreated melanoma without BRAF mutation. N. Engl. J. Med. 372, 320–330 (2015).
pubmed: 25399552
doi: 10.1056/NEJMoa1412082
Ribas, A. et al. Association of pembrolizumab with tumor response and survival among patients with advanced melanoma. JAMA 315, 1600–1609 (2016).
pubmed: 27092830
doi: 10.1001/jama.2016.4059
Hodi, F. S. et al. Nivolumab plus ipilimumab or nivolumab alone versus ipilimumab alone in advanced melanoma (CheckMate 067): 4-year outcomes of a multicentre, randomised, phase 3 trial. Lancet Oncol. 19, 1480–1492 (2018).
pubmed: 30361170
doi: 10.1016/S1470-2045(18)30700-9
Wolchok, J. D. et al. Long-term outcomes with nivolumab plus ipilimumab or nivolumab alone versus ipilimumab in patients with advanced melanoma. J. Clin. Oncol. 40, 127–137 (2022).
pubmed: 34818112
doi: 10.1200/JCO.21.02229
Hodi, F. S. et al. TMB and inflammatory gene expression associated with clinical outcomes following immunotherapy in advanced melanoma. Cancer Immunol. Res. 9, 1202–1213 (2021).
pubmed: 34389558
pmcid: 9414280
doi: 10.1158/2326-6066.CIR-20-0983
Pires da Silva, I. et al. Clinical models to define response and survival with Anti-PD-1 antibodies alone or combined with ipilimumab in metastatic melanoma. J. Clin. Oncol. 40, 1068–1080 (2022).
pubmed: 35143285
doi: 10.1200/JCO.21.01701
Hernando-Calvo, A. et al. Dynamics of clinical biomarkers as predictors of immunotherapy benefit in metastatic melanoma patients. Clin. Transl. Oncol. 23, 311–317 (2021).
pubmed: 32562197
doi: 10.1007/s12094-020-02420-9
Helvind, N. M. et al. Routine PET-CT scans provide early and accurate recurrence detection in asymptomatic stage IIB-III melanoma patients. Eur. J. Surg. Oncol. 47, 3020–3027 (2021).
pubmed: 34120809
doi: 10.1016/j.ejso.2021.06.011
Ayati, N. et al. The value of (18)F-FDG PET/CT for predicting or monitoring immunotherapy response in patients with metastatic melanoma: a systematic review and meta-analysis. Eur. J. Nucl. Med. Mol. Imaging 48, 428–448 (2021).
pubmed: 32728798
doi: 10.1007/s00259-020-04967-9
Ayati, N. et al. Predictive value and accuracy of [(18)F]FDG PET/CT modified response criteria for checkpoint immunotherapy in patients with advanced melanoma. Eur. J. Nucl. Med. Mol. Imaging 50, 2715–2726 (2023).
pubmed: 37140669
pmcid: 10317870
doi: 10.1007/s00259-023-06247-8
Kart, T. et al. Automated imaging-based abdominal organ segmentation and quality control in 20,000 participants of the UK Biobank and German National Cohort Studies. Sci. Rep. 12, 18733 (2022).
pubmed: 36333523
pmcid: 9636393
doi: 10.1038/s41598-022-23632-9
Bettegowda, C. et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 6, 224ra224 (2014).
doi: 10.1126/scitranslmed.3007094
Phallen, J. et al. Direct detection of early-stage cancers using circulating tumor DNA. Sci. Transl. Med. 9, eaan2415 (2017).
pubmed: 28814544
pmcid: 6714979
doi: 10.1126/scitranslmed.aan2415
Forschner, A. et al. Tumor mutation burden and circulating tumor DNA in combined CTLA-4 and PD-1 antibody therapy in metastatic melanoma—results of a prospective biomarker study. J. Immunother. Cancer 7, 180 (2019).
pubmed: 31300034
pmcid: 6625062
doi: 10.1186/s40425-019-0659-0
McEvoy, A. C. et al. Correlation between circulating tumour DNA and metabolic tumour burden in metastatic melanoma patients. BMC Cancer 18, 726 (2018).
pubmed: 29986670
pmcid: 6038195
doi: 10.1186/s12885-018-4637-6
Gangadhar, T. C. et al. Feasibility of monitoring advanced melanoma patients using cell-free DNA from plasma. Pigment Cell Melanoma Res. 31, 73–81 (2018).
pubmed: 28786531
doi: 10.1111/pcmr.12623
Kennedy, S. R. et al. Detecting ultralow-frequency mutations by duplex sequencing. Nat. Protoc. 9, 2586–2606 (2014).
pubmed: 25299156
pmcid: 4271547
doi: 10.1038/nprot.2014.170
Forshew, T. et al. Noninvasive identification and monitoring of cancer mutations by targeted deep sequencing of plasma DNA. Sci. Transl. Med. 4, 136ra168 (2012).
doi: 10.1126/scitranslmed.3003726
Wan, J. C. M. et al. ctDNA monitoring using patient-specific sequencing and integration of variant reads. Sci. Transl. Med. 12, eaaz8084 (2020).
pubmed: 32554709
doi: 10.1126/scitranslmed.aaz8084
Coombes, R. C. et al. Personalized detection of circulating tumor DNA antedates breast cancer metastatic recurrence. Clin. Cancer Res. 25, 4255–4263 (2019).
pubmed: 30992300
doi: 10.1158/1078-0432.CCR-18-3663
Kurtz, D. M. et al. Enhanced detection of minimal residual disease by targeted sequencing of phased variants in circulating tumor DNA. Nat. Biotechnol. 39, 1537–1547 (2021).
pubmed: 34294911
pmcid: 8678141
doi: 10.1038/s41587-021-00981-w
Abbosh, C. et al. Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA. Nature 616, 553–562 (2023).
pubmed: 37055640
pmcid: 7614605
doi: 10.1038/s41586-023-05776-4
Assaf, Z. J. F. et al. A longitudinal circulating tumor DNA-based model associated with survival in metastatic non-small-cell lung cancer. Nat. Med. 29, 859–868 (2023).
pubmed: 36928816
pmcid: 10115641
doi: 10.1038/s41591-023-02226-6
Newman, A. M. et al. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat. Med. 20, 548–554 (2014).
pubmed: 24705333
pmcid: 4016134
doi: 10.1038/nm.3519
Parikh, A. R. et al. Liquid versus tissue biopsy for detecting acquired resistance and tumor heterogeneity in gastrointestinal cancers. Nat. Med. 25, 1415–1421 (2019).
pubmed: 31501609
pmcid: 6741444
doi: 10.1038/s41591-019-0561-9
S3 - Leitlinie zur Diagnostik, Therapie und Nachsorge des Melanoms. J. Dtsch. Dermatol. Ges. 18, (2020).
Marczynski, G. T., Laus, A. C., Dos Reis, M. B., Reis, R. M. & Vazquez, V. L. Circulating tumor DNA (ctDNA) detection is associated with shorter progression-free survival in advanced melanoma patients. Sci. Rep. 10, 18682 (2020).
pubmed: 33122747
pmcid: 7596487
doi: 10.1038/s41598-020-75792-1
Marsavela, G. et al. Detection of clinical progression through plasma ctDNA in metastatic melanoma patients: a comparison to radiological progression. Br. J. Cancer 126, 401–408 (2022).
pubmed: 34373567
doi: 10.1038/s41416-021-01507-6
Marsavela, G. et al. Circulating tumor DNA predicts outcome from first-, but not second-line treatment and identifies melanoma patients who may benefit from combination immunotherapy. Clin. Cancer Res. 26, 5926–5933 (2020).
pubmed: 33067256
doi: 10.1158/1078-0432.CCR-20-2251
Braune, J. et al. Circulating tumor DNA allows early treatment monitoring in BRAF- and NRAS-mutant malignant melanoma. JCO Precis. Oncol. 4, 20–31 (2020).
pubmed: 35050727
doi: 10.1200/PO.19.00174
Eroglu, Z. et al. Circulating tumor DNA-based molecular residual disease detection for treatment monitoring in advanced melanoma patients. Cancer 129, 1723–1734 (2023).
pubmed: 36869646
doi: 10.1002/cncr.34716
Wagner, N. B., Forschner, A., Leiter, U., Garbe, C. & Eigentler, T. K. S100B and LDH as early prognostic markers for response and overall survival in melanoma patients treated with anti-PD-1 or combined anti-PD-1 plus anti-CTLA-4 antibodies. Br. J. Cancer 119, 339–346 (2018).
pubmed: 29950611
pmcid: 6070917
doi: 10.1038/s41416-018-0167-x
Flaus, A. et al. FDG PET biomarkers for prediction of survival in metastatic melanoma prior to anti-PD1 immunotherapy. Sci. Rep. 11, 18795 (2021).
pubmed: 34552135
pmcid: 8458464
doi: 10.1038/s41598-021-98310-3
Boerlin, A. et al. The prognostic value of a single, randomly timed circulating tumor DNA measurement in patients with metastatic melanoma. Cancers 14, 4158 (2022).
pubmed: 36077695
pmcid: 9455041
doi: 10.3390/cancers14174158
Seremet, T. et al. Undetectable circulating tumor DNA (ctDNA) levels correlate with favorable outcome in metastatic melanoma patients treated with anti-PD1 therapy. J. Transl. Med. 17, 303 (2019).
pubmed: 31488153
pmcid: 6727487
doi: 10.1186/s12967-019-2051-8
Eckardt, J. et al. TMB and BRAF mutation status are independent predictive factors in high-risk melanoma patients with adjuvant anti-PD-1 therapy. J. Cancer Res. Clin. Oncol. 149, 833–840 (2023).
pubmed: 35192052
doi: 10.1007/s00432-022-03939-w
Horak, P. et al. Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC). Genet. Med. 24, 986–998 (2022).
pubmed: 35101336
pmcid: 9081216
doi: 10.1016/j.gim.2022.01.001
Sturm, M., Schroeder, C. & Bauer, P. SeqPurge: highly-sensitive adapter trimming for paired-end NGS data. BMC Bioinform. 17, 208 (2016).
doi: 10.1186/s12859-016-1069-7
Mose, L. E., Perou, C. M. & Parker, J. S. Improved indel detection in DNA and RNA via realignment with ABRA2. Bioinformatics 35, 2966–2973 (2019).
pubmed: 30649250
pmcid: 6735753
doi: 10.1093/bioinformatics/btz033
Isensee, F., Jaeger, P. F., Kohl, S. A. A., Petersen, J. & Maier-Hein, K. H. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat. Methods 18, 203–211 (2021).
pubmed: 33288961
doi: 10.1038/s41592-020-01008-z
Gatidis, S. et al. A whole-body FDG-PET/CT Dataset with manually annotated tumor lesions. Sci. Data 9, 601 (2022).
pubmed: 36195599
pmcid: 9532417
doi: 10.1038/s41597-022-01718-3
Kustner, T. et al. Development of a hybrid-imaging-based prognostic index for metastasized-melanoma patients in whole-body 18F-FDG PET/CT and PET/MRI data. Diagnostics 12, 2102 (2022).
pubmed: 36140504
pmcid: 9498091
doi: 10.3390/diagnostics12092102
Im, H. J., Bradshaw, T., Solaiyappan, M. & Cho, S. Y. Current methods to define metabolic tumor volume in positron emission tomography: which one is better? Nucl. Med. Mol. Imaging 52, 5–15 (2018).
pubmed: 29391907
doi: 10.1007/s13139-017-0493-6