KS02.7.A THE IMPACT OF INTRAOPERATIVE NANOPORE SEQUENCING BASED MOLECULAR DIAGNOSIS ON SURGICAL DECISION-MAKING

Abstract BACKGROUND Despite the inability of preoperative imaging to clearly classify tumor entities many centers are not performing intraoperative frozen section pathology due to its lack of specificity. Nanopore sequencing enables methylation classification and copy-number variation analysis of tumor biopsies in a time-frame that falls within longer surgical operations. MATERIAL AND METHODS DNA was isolated from tumor tissue and sequenced on minion or promethion flow cells during surgery. Methylation data was analyzed using nanoDX/crossNN diagnostic pipeline. RESULTS Analysis was performed from 2020 to 2025 for 87 surgeries samples. The mean return-time from pick-up of the biopsy to report back to the OR was 76 mins (64-110 mins). A DNA-methylation based diagnosis was concluded above the suggested cut-off level in 75 cases. Data was generated form ultra-low coverage, generated from a mean of 2601 (range 519-9000) CpGs. In cases of uncertainty, CNV was used to support a suggested diagnosis. The result was compared to the suggested tumor entities based upon preoperative MRI. The intraoperative molecularly supported diagnosis was concordant with the final, layered diagnosis in >90% of cases. The intraoperative sequencing diagnostics was combined with intraoperative MRI imaging allowing for micro-MDT discussion on the cost-gain balance of further resection based upon tumor remnant and the molecular tumor subtype. The molecular diagnosis was supportive of a modulation of surgical resective strategy in >50% of surgeries - whether a more restrictive resection or a supramaximal/total resection was the adjusted, preferred aim. Updated data of the first 100 intraoperative analyses will be presented. CONCLUSION Intraoperative nanopore sequencing combined with an ad-hoc random forest or a neural-network based machine learning algorithm allows for molecular tumor classification in a robust, fast and sensitive manner. This preliminary report aims to support other centers to adapt the strategy with the aim of individualizing the surgical resective strategy risk vs. gain aimed for during surgery.

Authors

Institutions

Publication Details

Journal
Neuro-Oncology
Published
2025-10-01
DOI
https://doi.org/10.1093/neuonc/noaf193.024
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

KS02.7.A THE IMPACT OF INTRAOPERATIVE NANOPORE SEQUENCING BASED MOLECULAR DIAGNOSIS ON SURGICAL DECISION-MAKING

Skarphéðinn Halldórsson, Henning Leske, Philipp Euskirchen, Einar Osland Vik-Mo et al.
Neuro-Oncology
Cancer Genomics and Diagnostics
article

KS02.7.A THE IMPACT OF INTRAOPERATIVE NANOPORE SEQUENCING BASED MOLECULAR DIAGNOSIS ON SURGICAL DECISION-MAKING

Skarphéðinn Halldórsson, Henning Leske, Philipp Euskirchen, Einar Osland Vik-Mo, Richárd Nagymihály, Bernt Johan Due‐Tønnessen
article en

Abstract

Abstract BACKGROUND Despite the inability of preoperative imaging to clearly classify tumor entities many centers are not performing intraoperative frozen section pathology due to its lack of specificity. Nanopore sequencing enables methylation classification and copy-number variation analysis of tumor biopsies in a time-frame that falls within longer surgical operations. MATERIAL AND METHODS DNA was isolated from tumor tissue and sequenced on minion or promethion flow cells during surgery. Methylation data was analyzed using nanoDX/crossNN diagnostic pipeline. RESULTS Analysis was performed from 2020 to 2025 for 87 surgeries samples. The mean return-time from pick-up of the biopsy to report back to the OR was 76 mins (64-110 mins). A DNA-methylation based diagnosis was concluded above the suggested cut-off level in 75 cases. Data was generated form ultra-low coverage, generated from a mean of 2601 (range 519-9000) CpGs. In cases of uncertainty, CNV was used to support a suggested diagnosis. The result was compared to the suggested tumor entities based upon preoperative MRI. The intraoperative molecularly supported diagnosis was concordant with the final, layered diagnosis in >90% of cases. The intraoperative sequencing diagnostics was combined with intraoperative MRI imaging allowing for micro-MDT discussion on the cost-gain balance of further resection based upon tumor remnant and the molecular tumor subtype. The molecular diagnosis was supportive of a modulation of surgical resective strategy in >50% of surgeries - whether a more restrictive resection or a supramaximal/total resection was the adjusted, preferred aim. Updated data of the first 100 intraoperative analyses will be presented. CONCLUSION Intraoperative nanopore sequencing combined with an ad-hoc random forest or a neural-network based machine learning algorithm allows for molecular tumor classification in a robust, fast and sensitive manner. This preliminary report aims to support other centers to adapt the strategy with the aim of individualizing the surgical resective strategy risk vs. gain aimed for during surgery.

Neuro-OncologyVol. 27(Supplement_3)
Oslo University Hospital (NO), Charité - Universitätsmedizin Berlin (DE)
Openalex Percentile: Top 66%
Cancer Genomics and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.