TY - GEN
T1 - Elucidating Cancer Subtypes by Using Epigenome and Genome Cross-Talk
AU - Jilani, Muneeba
AU - Haspel, Nurit
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - DNA methylation plays a critical role in tumorigenesis and tumor malignancy . The role of this epigenetic phenomena, especially, in the investigation of cancer subtypes remains rather under-explored. In this study, we use sCClust (sparse Canonical Correlation analysis with Clustering), a method that combines high-dimensional omics data using sparse canonical correlation analysis (sCCA), to gene expression and DNA methylation data for prostate cancer to elucidate underlying subtypes. We compare the subtypes with the TCGA taxonomy and evaluate the results using survival analysis. Our findings demonstrate that data integration results in statistically significant subtypes similar to the TCGA subtypes and outperforms existing classification efforts. The significance of this study lies in enhancement in the subtyping of prostate cancer, as well as statistical integration of epigenomic and transcriptomic data.
AB - DNA methylation plays a critical role in tumorigenesis and tumor malignancy . The role of this epigenetic phenomena, especially, in the investigation of cancer subtypes remains rather under-explored. In this study, we use sCClust (sparse Canonical Correlation analysis with Clustering), a method that combines high-dimensional omics data using sparse canonical correlation analysis (sCCA), to gene expression and DNA methylation data for prostate cancer to elucidate underlying subtypes. We compare the subtypes with the TCGA taxonomy and evaluate the results using survival analysis. Our findings demonstrate that data integration results in statistically significant subtypes similar to the TCGA subtypes and outperforms existing classification efforts. The significance of this study lies in enhancement in the subtyping of prostate cancer, as well as statistical integration of epigenomic and transcriptomic data.
KW - Cancer Subtypes
KW - Data Integration
KW - DNA Methylation
KW - Prostate Adenocarcinoma
UR - https://www.scopus.com/pages/publications/85202622850
UR - https://www.scopus.com/pages/publications/85202622850#tab=citedBy
U2 - 10.1007/978-3-031-64629-4_1
DO - 10.1007/978-3-031-64629-4_1
M3 - Conference contribution
AN - SCOPUS:85202622850
SN - 9783031646287
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 3
EP - 16
BT - Bioinformatics and Biomedical Engineering - 11th International Conference, IWBBIO 2024, Proceedings
A2 - Rojas, Ignacio
A2 - Ortuño, Francisco
A2 - Rojas, Fernando
A2 - Herrera, Luis Javier
A2 - Valenzuela, Olga
PB - Springer Science and Business Media Deutschland GmbH
T2 - 11th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2024
Y2 - 15 July 2024 through 17 July 2024
ER -