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Updated: Jun 1, 2025
Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
Nanopore-based random genomic sampling for intraoperative molecular diagnosis
Francesco E Emiliani1,2, Abdol Aziz Ould Ismail1, Edward G Hughes1
1Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA.
Background:
Central nervous system tumors are among the most lethal types of cancer. A critical factor for tailored neurosurgical resection strategies depends on specific tumor types. However, it is uncommon to have a preoperative tumor diagnosis, and intraoperative morphology-based diagnosis remains challenging. Despite recent advances in intraoperative methylation classifications of brain tumors, accuracy may be compromised by low tumor purity. Copy number variations (CNVs), which are almost ubiquitous in cancer, offer highly sensitive molecular biomarkers for diagnosis. These quantitative genomic alterations provide insight into dysregulated oncogenic pathways and can reveal potential targets for molecular therapies.
Methods:
We develop iSCORED, a one-step random genomic DNA reconstruction method that enables efficient, unbiased quantification of genome-wide CNVs. By concatenating multiple genomic fragments into long reads, the method leverages low-pass sequencing to generate approximately 1-2 million genomic fragments within 1 h. This approach allows for ultrafast high-resolution CNV analysis at a genomic resolution of 50 kb. In addition, concurrent methylation profiling enables brain tumor methylation classification and identifies promoter methylation in amplified oncogenes, providing an integrated diagnostic approach.
Results:
In our retrospective cohort of 26 malignant brain tumors, iSCORED demonstrated 100% concordance in CNV detection, including chromosomal alterations and oncogene amplifications, when compared to clinically validated assays such as Next-Generation Sequencing and Chromosomal Microarray. Furthermore, we validated iSCORED's real-time applicability in 15 diagnostically challenging primary brain tumors, achieving 100% concordance in detecting aberrant CNV detection, including diagnostic chromosomal gains/losses and oncogene amplifications (10/10). Of these, 14 out of 15 brain tumor methylation classifications aligned with final pathological diagnoses. This streamlined workflow-from tissue arrival to automatic generation of CNV and methylation reports-can be completed within 105 min.
Conclusions:
The iSCORED pipeline represents the first method capable of high-resolution CNV detection within the intraoperative timeframe. By combining CNV detection and methylation classification, iSCORED provides a rapid and comprehensive molecular diagnostic tool that can inform rapid clinical decision. The integrated approach not only enhances the accuracy of tumor diagnosis but also optimizes surgical planning and identifies potential molecular therapies, all within the critical intraoperative timeframe.
Insights
iSCORED enables rapid, high-resolution copy number variation (CNV) detection and methylation classification for brain tumors. This integrated approach improves intraoperative diagnosis and surgical planning for improved patient outcomes.
Area of Science:
- Neuro-oncology
- Genomics
- Molecular Diagnostics
Background:
- Central nervous system tumors are highly lethal, necessitating accurate preoperative and intraoperative diagnosis for effective surgical resection.
- Current intraoperative diagnostic methods, including methylation classification, can be limited by low tumor purity and challenging morphology-based assessments.
- Copy number variations (CNVs) are sensitive molecular biomarkers that offer insights into oncogenic pathways and potential therapeutic targets.
Purpose of the Study:
- To develop and validate iSCORED, a novel method for rapid, high-resolution genome-wide copy number variation (CNV) quantification.
- To integrate CNV detection with methylation profiling for a comprehensive intraoperative brain tumor diagnostic approach.
- To assess the accuracy and efficiency of iSCORED in comparison to established diagnostic techniques.
Main Methods:
- iSCORED utilizes a one-step random genomic DNA reconstruction method to concatenate genomic fragments into long reads for low-pass sequencing.
- The method achieves ultrafast (1-hour) high-resolution (50 kb) CNV analysis by generating approximately 1-2 million genomic fragments.
- Concurrent methylation profiling is performed to enable brain tumor classification and identify promoter methylation in amplified oncogenes.
Main Results:
- iSCORED demonstrated 100% concordance with Next-Generation Sequencing and Chromosomal Microarray for CNV detection in a retrospective cohort of 26 malignant brain tumors.
- Real-time validation in 15 challenging primary brain tumors showed 100% concordance in aberrant CNV detection, including gains/losses and oncogene amplifications.
- The complete workflow, from tissue arrival to report generation, was completed within 105 minutes, with 14 out of 15 methylation classifications aligning with final pathological diagnoses.
Conclusions:
- iSCORED is the first method providing high-resolution CNV detection within the intraoperative timeframe.
- The integrated CNV detection and methylation classification offers a rapid and comprehensive molecular diagnostic tool for intraoperative decision-making.
- This approach enhances diagnostic accuracy, optimizes surgical planning, and identifies potential molecular therapies during surgery.
