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Evaluation of Bridge Capture technology for mutation profiling in liquid biopsies of metastatic colorectal cancer patients

Ganesan, Aparna; Korkiakoski, Anttoni; Adamusová, Simona; Musku, Anna; Rantasalo, Tuula; Laine, Nea; Andersson, Emma; Osterlund, Emerik; Ovissi, Ali; Halonen, Päivi; Hirvonen, Tatu; Kim, Jorma; Laine, Jukka; Silvoniemi, Antti; Minn, Heikki; Blomster, Juuso; Anttonen, Anna-Kaisa; Kytölä, Soili; Osterlund, Pia; Pursiheimo, Juha-Pekka; Nummela, Pirjo; Tamminen, Manu; Ristimäki, Ari

Evaluation of Bridge Capture technology for mutation profiling in liquid biopsies of metastatic colorectal cancer patients

Ganesan, Aparna
Korkiakoski, Anttoni
Adamusová, Simona
Musku, Anna
Rantasalo, Tuula
Laine, Nea
Andersson, Emma
Osterlund, Emerik
Ovissi, Ali
Halonen, Päivi
Hirvonen, Tatu
Kim, Jorma
Laine, Jukka
Silvoniemi, Antti
Minn, Heikki
Blomster, Juuso
Anttonen, Anna-Kaisa
Kytölä, Soili
Osterlund, Pia
Pursiheimo, Juha-Pekka
Nummela, Pirjo
Tamminen, Manu
Ristimäki, Ari
Katso/Avaa
s41598-025-04827-2.pdf (18.93Mb)
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NATURE PORTFOLIO
doi:10.1038/s41598-025-04827-2
URI
https://www.nature.com/articles/s41598-025-04827-2
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2025082792701
Tiivistelmä

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths, often presenting at an advanced stage with significant molecular heterogeneity. This is the first study to evaluate the performance of a novel next-generation sequencing (NGS)-based Bridge Capture technology for mutation profiling and minimal residual disease detection in circulating tumor (ct)DNA from metastatic colorectal cancer (mCRC) patients. Its performance was compared to those of droplet digital PCR (ddPCR), Ion AmpliSeq Cancer Hotspot Panel v2, and Idylla ctKRAS Mutation Assay. Eighty serial plasma samples from ten mCRC patients were analyzed by Bridge Capture and ddPCR, demonstrating a very strong correlation in variant allele frequency (VAF) values (rs = 0.86). The concordance of Bridge Capture with ddPCR (kappa = 0.70) and Idylla (kappa = 0.79) showed substantial agreement. A subset of samples (n = 10) was analyzed using the Ion AmpliSeq NGS-panel and both methods identified 15 driver mutations with strong correlation of VAF values (rs = 0.74). Additionally, Bridge Capture identified several oncogenic mutations beyond those detected by Ion AmpliSeq, highlighting its comprehensive profiling capability. The scalability of Bridge Capture was validated using an expanded panel and synthetic DNA targets, showing a strong linear correlation between observed and expected VAF values. This study demonstrates the scalability and accuracy of the Bridge Capture platform, and its potential to enhance mutation detection and clinical decision-making using ctDNA samples from patients with mCRC.

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