한빛사논문
- 조회406
Seulki Song 1,2,†, Youngil Koh 1,3,†, Seokhyeon Kim 1,†, Sang Mi Lee 4, Hyun Uk Kim 4,*, Jung Min Ko 5,*, Se‑Hoon Lee 6 *, Sung‑Soo Yoon 1,3,* and Solip Park 2,*
1Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
2Structural Biology Program, Centro Nacional de Investigaciones Oncológicas (CNIO), Calle de Melchor Fernández Almagro, 3, Madrid 28029, Spain.
3Biomedical Research Institute and Departments of Internal Medicine, Seoul National University Hospital, Seoul 03080, Republic of Korea.
4Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
5Department of Pediatrics, Seoul National University Children’s Hospital, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
6Division of Hematology‑Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea.
†Seulki Song, Youngil Koh and Seokhyeon Kim contributed equally to this work
*Corresponding authors: correspondence to Hyun Uk Kim, Jung Min Ko, Se‑Hoon Lee, Sung‑Soo Yoon or Solip Park
Abstract
Background
Despite the acceleration of somatic driver gene discovery facilitated by recent large-scale tumor sequencing data, the contribution of inherited variants remains largely unexplored, primarily focusing on previously known cancer predisposition genes (CPGs) due to the low statistical power associated with detecting rare pathogenic variant-phenotype associations.
Methods
Here, we introduce a generalized log-regression model to measure the excess of pathogenic variants within genes in cancer patients compared to control samples. It aims to measure gene-level cancer risk enrichment by collapsing rare pathogenic variants after controlling the population differences across samples.
Results
In this study, we investigate whether pathogenic variants in Mendelian disease-associated genes (OMIM genes) are enriched in cancer patients compared to controls. Utilizing data from PCAWG and the 1,000 Genomes Project, we identify 103 OMIM genes demonstrating significant enrichment of pathogenic variants in cancer samples (FDR 20%). Through an integrative approach considering three distinct properties, we classify these CPG-like OMIM genes into four clusters, indicating potential diverse mechanisms underlying tumor progression. Further, we explore the function of PAH (a key metabolic enzyme associated with Phenylketonuria), the gene exhibiting the highest prevalence of pathogenic variants in a pan-cancer (1.8%) compared to controls (0.6%).
Conclusions
Our findings suggest a possible cancer progression mechanism through metabolic profile alterations. Overall, our data indicates that pathogenic OMIM gene variants contribute to cancer progression and introduces new CPG classifications potentially underpinning diverse tumorigenesis mechanisms.
논문정보
- Research article
- 2023년 12월 (BRIC 등록일 2024-02-07)
- 국내+국외 연구진
- 바이오·의료융합 > 다학제 융합/복합
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