AUTHOR=Feng Jie , Jiang Limin , Li Shuhao , Tang Jijun , Wen Lan 

TITLE=Multi-Omics Data Fusion via a Joint Kernel Learning Model for Cancer Subtype Discovery and Essential Gene Identification

JOURNAL=Frontiers in Genetics

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.647141

DOI=10.3389/fgene.2021.647141

ISSN=1664-8021

ABSTRACT=The multiple-source of cancer determine its multiple causes, and the same cancer can be composed of many different subtypes. Identification of cancer subtypes is a key part of personalized cancer treatment, and provides an important reference for clinical diagnosis and treatment. Some studies have shown that there are significant differences in the genetic and epigenetic profiles among different cancer subtypes during carcinogenesis and development. In this study, we first collect seven cancer datasets from the TCGA dataset of the Broad Institute GDAC Firehose, including gene expression profile, isoform expression profile, DNA methylation expression data and survival information correspondingly. Furthermore, we employ kernel PCA to extract features for each expression profile, and convert them into three similarity kernel matrices by Gaussian kernel function, then fuse these matrices as a global kernel matrix. Finally, we apply spectral clustering algorithm on fusion kernel matrix to obtain the clustering on different cancer subtypes. In the experimental results, besides using the P-value from the Cox regression model and survival analysis as the primary evaluation measures, we also introduce statistical indicators such as RI and ARI to verify the performance of clustering itself. Then combining with gene expression profile, we obtain the differential expression of genes among different subtypes by gene set enrichment analysis. For lung cancer, GMPS, EPHA10, C10orf54 and MAGEA6 are highly expressed in different subtypes; for liver cancer, CMYA5, DEPDC6, FAU, VPS24, RCBTB2, LOC100133469 and SLC35B4 are significantly expressed in different subtypes.