Personalized oncogenomic analysis of metastatic adenoid cystic carcinoma: using whole-genome sequencing to inform clinical decision-making

Abstract

Metastatic adenoid cystic carcinomas (ACCs) can cause significant morbidity and mortality. Because of their slow growth and relative rarity, there is limited evidence for systemic therapy regimens. Recently, molecular profiling studies have begun to reveal the genetic landscape of these poorly understood cancers, and new treatment possibilities are beginning to emerge. The objective is to use whole-genome and transcriptome sequencing and analysis to better understand the genetic alterations underlying the pathology of metastatic and rare ACCs and determine potentially actionable therapeutic targets. We report five cases of metastatic ACC, not originating in the salivary glands, in patients enrolled in the Personalized Oncogenomics (POG) Program at the BC Cancer Agency. Genomic workup included whole-genome and transcriptome sequencing, detailed analysis of tumor alterations, and integration with existing knowledge of drug–target combinations to identify potential therapeutic targets. Analysis reveals low mutational burden in these five ACC cases, and mutation signatures that are commonly observed in multiple cancer types. Notably, the only recurrent structural aberration identified was the well-described MYB-NFIB fusion that was present in four of five cases, and one case exhibited a closely related MYBL1-NFIB fusion. Recurrent mutations were also identified in BAP1 and BCOR, with additional mutations in individual samples affecting NOTCH1 and the epigenetic regulators ARID2, SMARCA2, and SMARCB1. Copy changes were rare, and they included amplification of MYC and homozygous loss of CDKN2A in individual samples. Genomic analysis revealed therapeutic targets in all five cases and served to inform a therapeutic choice in three of the cases to date.

Clinically Integrated Molecular Diagnostics in Adenoid Cystic Carcinoma

“…A key factor in maintaining an integrated genotyping program in clinical practice is achieving financial sustainability. In contrast to cancers with higher prevalence, the rarity in orphan diseases poses additional hurdles , particularly when genotyping is applied only to the meaningful subsets of patients. During the initial phase (2013–2015; Fig.…”

“…Molecular genotyping in ACC is primarily performed in research settings, and numerous studies have outlined relevant mutational profiles [17,[57][58][59]. In addition, various biological [12,17,60], diagnostic [60][61][62][63][64], prognostic [16,54,64], and therapeutic advances [14,15,59] have been proposed. It is important to note that our study did not focus on identification or description of novel biomarkers.…”

“…Numerous studies have delineated key molecular profiles of ACC [8][9][10][11][12][13] and collectively indicate pathways for genotype-stratified therapies [14][15][16][17][18]. The concept, to match each patient according to the tumor pathway profile to the most effective (biologically sound) and least toxic treatment, rests on the prevalence of actionable alterations [14,[19][20][21]. Assessment of established alterations in clinical practice requires comprehensive genotyping efforts, for example, accomplished via next-generation sequencing (NGS) technologies.…”

“…Through institutional prioritization, we have initiated pan‐cancer genetic testing in 2008, transitioned to NGS‐based testing in 2011, and adopted specific NGS billing codes in 2015. In common cancers, the identification of rare subsets of actionable targets has been established (e.g., National Comprehensive Cancer Network [NCCN], College of American Pathologists guidelines); however, the need for more effective, biomarker‐informed therapies in a disease as rare as ACC poses unique challenges to demonstrate clinical utility and U.S.‐centric financial sustainability .…”

Application of a Neural Network Whole Transcriptome–Based Pan-Cancer Method for Diagnosis of Primary and Metastatic Cancers

“…As demonstrated by previous studies, SCOPE has proven valuable for orthogonal assessment of common cancers 26 and for contextualizing the biological features of complex, rare cancer types. 37 As shown by its performance on CUPs, it is particularly useful in expediting precision oncology workflows and in clinical laboratories where access to a plethora of immunostains for sequential diagnosis may be limited.…”