PathMethy: an interpretable AI framework for cancer origin tracing based on DNA methylation

Despite advanced diagnostics, 3%-5% of cases remain classified as cancer of unknown primary (CUP). DNA methylation, an important epigenetic feature, is essential for determining the origin of metastatic tumors. We presented PathMethy, a novel Transformer model integrated with functional categories and crosstalk of pathways, to accurately trace the origin of tumors in CUP samples based on DNA methylation. PathMethy outperformed seven competing methods in F1-score across nine cancer datasets and predicted accurately the molecular subtypes within nine primary tumor types. It not only excelled at tracing the origins of both primary and metastatic tumors but also demonstrated a high degree of agreement with previously diagnosed sites in cases of CUP. PathMethy provided biological insights by highlighting key pathways, functional categories, and their interactions. Using functional categories of pathways, we gained a global understanding of biological processes. For broader access, a user-friendly web server for researchers and clinicians is available at https://cup.pathmethy.com.

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Publication Details

Journal
Briefings in Bioinformatics
Published
2024-09-23
DOI
https://doi.org/10.1093/bib/bbae497
Citations
3
Primary Topic
Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.85

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article

PathMethy: an interpretable AI framework for cancer origin tracing based on DNA methylation

Mengsha Tong, Jiajing Xie, Rongshan Yu, Shijie Luo et al.
3 citations
Briefings in Bioinformatics
Cancer Diagnosis and Treatment
0.85
article

PathMethy: an interpretable AI framework for cancer origin tracing based on DNA methylation

Mengsha Tong, Jiajing Xie, Rongshan Yu, Shijie Luo, Hailong Zheng, Ying Chen, Chen Zhang, Yu-Hang Song
article en
3 citations

Abstract

Despite advanced diagnostics, 3%-5% of cases remain classified as cancer of unknown primary (CUP). DNA methylation, an important epigenetic feature, is essential for determining the origin of metastatic tumors. We presented PathMethy, a novel Transformer model integrated with functional categories and crosstalk of pathways, to accurately trace the origin of tumors in CUP samples based on DNA methylation. PathMethy outperformed seven competing methods in F1-score across nine cancer datasets and predicted accurately the molecular subtypes within nine primary tumor types. It not only excelled at tracing the origins of both primary and metastatic tumors but also demonstrated a high degree of agreement with previously diagnosed sites in cases of CUP. PathMethy provided biological insights by highlighting key pathways, functional categories, and their interactions. Using functional categories of pathways, we gained a global understanding of biological processes. For broader access, a user-friendly web server for researchers and clinicians is available at https://cup.pathmethy.com.

Briefings in BioinformaticsVol. 25(6)
Xiamen University (CN), Guangdong Baiyun University (CN), Southern Medical University (CN)
National Natural Science Foundation of China, Xiamen University
Openalex Percentile: Top 22%
Cancer Diagnosis and Treatment
0.85
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PathMethy: an interpretable AI framework for cancer origin tracing based on DNA methylation — Mengsha Tong, Jiajing Xie, et al. · Briefings in Bioinformatics (2024) | TGRS Research Map | TGRS