Molecular diagnosis has become highly significant for patient management in oncology.
Here, 30 well-characterized clinical germline samples were studied with adaptive sampling to enrich the full sequence of 152 cancer predisposition genes. Sequencing was performed on Oxford Nanopore (ONT) R10.4.1 MinION flowcells with the Q20+ chemistry.
In our cohort, 11 samples had large-scale rearrangements (LSR), which were all detected with ONT sequencing. In addition to perfectly detecting the locus of the LSR, we found a known MLPA amplification of exon 13 in the BRCA1 (NM_7294) gene corresponded to a duplication in tandem of both exons 12 and 13 of the reference NM_7300. Similarly, in another sample with a known total deletion of the BRCA1 gene, ONT sequencing highlighted this complete deletion was the consequence of a large deletion of almost 140 000 bp carrying over five different genes. ONT sequencing was also able to detect all pathogenic nucleotide variants present in 16 samples at low coverage. As we analyzed complete genes and more genes than with short-read sequencing, we detected novel unknown variants. We randomly selected six new variants with a coverage larger than 10× and an average quality higher than 14, and confirmed all of them by Sanger sequencing, suggesting that variants detected with ONT (coverage >10× and quality score >14) could be considered as real variants.
We showed that ONT adaptive sampling sequencing is suitable for the analysis of germline alterations, improves characterization of LSR, and detects single nucleotide variations even at low coverage.
Multi-omics features of cell-free DNA (cfDNA) can effectively improve the performance of non-invasive early diagnosis and prognosis of cancer. However, multimodal characterization of cfDNA remains technically challenging.
We developed a comprehensive multi-omics solution (COMOS) to specifically obtain an extensive fragmentomics landscape, presented by breakpoint characteristics of nucleosomes, CpG islands, DNase clusters and enhancers, besides typical methylation, copy number alteration of cfDNA. The COMOS was tested on 214 plasma samples of diffuse large B-cell lymphoma (DLBCL) and matched healthy controls.
For early diagnosis, COMOS improved the area under the curve (AUC) value to .993 compared with the individual omics model, with a sensitivity of 95% at 98% specificity. Detection sensitivity achieved 91% at 99% specificity in early-stage patients, while the AUC values of the individual omics model were 0.942, 0.968, 0.989, 0.935, 0.921, 0.781 and 0.917, respectively, with lower sensitivity and specificity. In the treatment response cohort, COMOS yielded a superior sensitivity of 88% at 86% specificity (AUC, 0.903). COMOS has achieved excellent performance in early diagnosis and treatment response prediction.
Our study provides an effectively improved approach with high accuracy for the diagnosis and prognosis of DLBCL, showing great potential for future clinical application.
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