Patient-specific genomic profiling for advanced cancers in young adults

Abstract

Purpose: Although adolescent and young adult (AYA) cancers are characterized by biological features and clinical outcomes distinct from those of other age groups, the molecular profile of AYA cancers has not well been defined. In this study, I analyzed cancer genomes from rare types of metastatic AYA cancer patients to identify candidate driving and/or druggable genetic alterations. Methods: Pattern-based heuristic annotation was developed to identify candidate driving genetic alterations from processed sequencing data of individual cancer genome. The reliability of the approach was validated by applying to whole exome sequencing (WES) data of acute myeloid leukemia (AML) from The Cancer Genome Atlas (TCGA). Then, prospectively collected AYA tumor samples from seven different patients were analyzed using three different genomics platforms (whole-exome sequencing, whole-transcriptome sequencing or OncoScanTM). By using well-known bioinformatics tools (bwa, Picard, GATK, MuTect, and Somatic Indel Detector) and the pattern-based heuristic annotation approach with open access databases (DAVID and DGIdb), I processed sequencing data and identified candidate driving genetic alterations with their druggability specific to each patient. Results: Using pattern-based heuristic annotation, all candidate genes were confirmed which was described in published data of TCGA AML study as well as additional candidates such as MYC, NF1 and ARID2. In AYA cancers, the mutation frequencies were lower than those of other adult cancers (median=0.56), except for a germ cell tumor with hypermutation. Patient-specific genetic alterations in candidate driving genes were idendified: RASA2 and NF1 (prostate cancer), TP53 and CDKN2C (olfactory neuroblastoma), FAT1, NOTCH1, and SMAD4 (head and neck cancer), KRAS (urachal carcinoma), EML4-ALK (lung cancer), and MDM2 and PTEN (liposarcoma). Under consult of clinicians, potential drugs were suggested for each patient according to his or her altered genes or related pathways. By comparing candidate driving genes between AYA cancers and those from all age groups for the same type of cancer, different driving genes were identified in prostate cancer and a germ cell tumor in AYAs compared with all age groups, whereas three common alterations (TP53, FAT1, and NOTCH1) in head and neck cancer were identified in both groups. Conclusion: This study identified patient-specific genetic alterations with druggability of seven rare types of AYA cancers and showed importance and feasibility of analysis of individual cancer genome. Additionally, it showed genetic alterations in cancers from AYA and those from all age groups varied by cancer type.