Mutational Signature and Transcriptomic Classification Analyses as the Decisive Diagnostic Tools for a Cancer of Unknown Primary

Abstract

PURPOSE Cancer of unknown primary is a group of metastatic tumors in which the standard diagnostic workup fails to identify the site of origin of the tumor. The potential impact of precision oncology on this group of patients is large, because actionable driver mutations and a correct diagnosis could provide treatment options otherwise not available for patients with these fatal cancers. This study investigated if comprehensive genomic analyses could provide information on the origin of the tumor. PATIENTS AND METHODS Here we describe a patient whose tumor was misdiagnosed at least three times. Next-generation sequencing, a patient-derived xenograft mouse model, and bioinformatics were used to identify an actionable mutation, predict resistance development to the targeted therapy, and correctly diagnose the origin of the tumor. Transcriptomic classification was benchmarked using The Cancer Genome Atlas (TCGA). RESULTS Despite the lack of a known primary tumor site and the absence of diagnostic immunohistochemical markers, the origin of the patient's tumor was established using the novel bioinformatic workflow. This included a mutational signature analysis of the sequenced metastases and comparison of their transcriptomic profiles to a pan-cancer panel of tumors from TCGA. We further discuss the strengths and limitations of the latter approaches in the context of three potentially incorrectly diagnosed TCGA lung tumors. CONCLUSION Comprehensive genomic analyses can provide information on the origin of tumors in patients with cancer of unknown primary.