Dataset Information

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.

SUBMITTER: Bagge RO

PROVIDER: S-EPMC7446430 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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

Bagge Roger Olofsson RO Demir Akif A Karlsson Joakim J Alaei-Mahabadi Babak B Einarsdottir Berglind O BO Jespersen Henrik H Lindberg Mattias F MF Muth Andreas A Nilsson Lisa M LM Persson Marta M Svensson Johanna B JB Söderberg Elin M V EMV de Krijger Ronald R RR Nilsson Ola O Larsson Erik E Stenman Göran G Nilsson Jonas A JA

JCO precision oncology 20180730

<h4>Purpose</h4>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 ...[more]

PMID: 32913988

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Project description:BackgroundRoughly 5% of metastatic cancers present with uncertain origin, for which molecular classification could influence subsequent management; however, prior studies of molecular diagnostic classifiers have reported mixed results with regard to clinical impact. In this retrospective study, we evaluated the utility of a novel molecular diagnostic classifier by assessing theoretical changes in treatment and additional testing recommendations from oncologists before and after the review of classifier predictions.MethodsWe retrospectively analyzed de-identified records from 289 patients with a consensus diagnosis of cancer of uncertain/unknown primary (CUP). Two (or three, if adjudication was required) independent oncologists separately reviewed patient clinical information to determine the course of treatment before they reviewed results from the molecular diagnostic classifier and subsequently evaluated whether the predicted diagnosis would alter their treatment plan.ResultsResults from the molecular diagnostic classifier changed the consensus oncologist-reported treatment recommendations for 235 out of 289 patients (81.3%). At the level of individual oncologist reviews (n = 414), 64.7% (n = 268) of treatment recommendations were based on CUP guidelines prior to review of results from the molecular diagnostic classifier. After seeing classifier results, 98.1% (n = 207) of the reviews, where treatment was specified (n = 211), were guided by the tissue of origin-specific guidelines. Overall, 89.9% of the 414 total reviews either expressed strong agreement (n = 242) or agreement (n = 130) that the molecular diagnostic classifier result increased confidence in selecting the most appropriate treatment regimen.ConclusionsA retrospective review of CUP cases demonstrates that a novel molecular diagnostic classifier could affect treatment in the majority of patients, supporting its clinical utility. Further studies are needed to prospectively evaluate whether the use of molecular diagnostic classifiers improves clinical outcomes in CUP patients.

Dataset Information

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

Publications

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

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