Identifying Cancer Type-Specific Transcriptional Programs through Network Analysis

SIMPLE SUMMARY: This study focused on identifying cancer type-specific genes, which are crucial for improving the detection, diagnosis, and treatment of various types of cancer. We used a network biology framework to explore the expression of transcription factors in different types of cancer. By comparing gene networks in normal cells with those in cancer cells, we were able to identify cancer type-specific genes. This offers a resource for understanding transcriptional networks across various cancer types. ABSTRACT: Identifying cancer type-specific genes that define cell states is important to develop effective therapies for patients and methods for detection, early diagnosis, and prevention. While molecular mechanisms that drive malignancy have been identified for various cancers, the identification of cell-type defining transcription factors (TFs) that distinguish normal cells from cancer cells has not been fully elucidated. Here, we utilized a network biology framework, which assesses the fidelity of cell fate conversions, to identify cancer type-specific gene regulatory networks (GRN) for 17 types of cancer. Through an integrative analysis of a compendium of expression data, we elucidated core TFs and GRNs for multiple cancer types. Moreover, by comparing normal tissues and cells to cancer type-specific GRNs, we found that the expression of key network-influencing TFs can be utilized as a survival prognostic indicator for a diverse cohort of cancer patients. These findings offer a valuable resource for exploring cancer type-specific networks across a broad range of cancer types.