Integrated Multi-Omics Analysis for Somatic-Germline Interaction in Pheochromocytoma and Paraganglioma

Shan Chen, The University of Texas School of Public Health

Abstract

Pheochromocytoma and Paraganglioma (PCC/PGL) is one of the rarest cancers, with the highest degree of inheritability among all cancer types. We sought to identify the genetic etiology of PCC/PGL through a multi-omics and integrated analysis for susceptibility gene discovery and cancer driver identification. We employed the TCGA PCC/PGL cohort to profile genome-wide single nucleotide variations (SNVs), small deletion or insertion (INDELs), copy number variations (CNAs) and transcriptome changes to elucidate the genetic alterations in this cancer. Blood Whole-Exome Sequencing (WES) were utilized to identify susceptibility gene using VAAST 2.0, an algorithm that incorporates allele frequencies and damaging scores for rare variant association. SDHB was ranked No.1 by VAAST 2.0 and was the only one reaching genome-wide significance. All the other top 5 genes were known classical PCC/PGL genes, confirming the validity of our approach. Transcriptome analysis showed down-regulation of NF1 and SDHB associated with germline mutations in these genes. Significant RET up-regulation was found in patients with germline RET mutations, indicating an oncogenic role in PCC/PGL. Loss of copy number in all known genes expect RET significantly reduced their expressions in the tumors, while gain of copy number in NF1 and EGLN1 increased the expressions. Overall, our study provided a comprehensive view of the genomic alterations at single nucleotide level for DNA and RNA for PCC/PGL patients. The findings would provide important insights to advance clinical diagnosis or to develop targeted therapies for PCC/PGL patients.

Subject Area

Biostatistics

Recommended Citation

Chen, Shan, "Integrated Multi-Omics Analysis for Somatic-Germline Interaction in Pheochromocytoma and Paraganglioma" (2017). Texas Medical Center Dissertations (via ProQuest). AAI10620282.
https://digitalcommons.library.tmc.edu/dissertations/AAI10620282

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