ABSTRACT
IMPORTANCE: The risk stratification of adrenocortical carcinoma (ACC) based on tumor proliferation index and stage is limited. Adjuvant therapy after surgery is recommended for most patients. Pan-genomic studies have identified distinct molecular groups closely associated with outcome. OBJECTIVE: To compare the molecular classification for prognostic assessment of ACC with other known prognostic factors. DESIGN, SETTING, AND PARTICIPANTS: In this retrospective biomarker analysis, ACC tumor samples from 368 patients who had undergone surgical tumor removal were collected from March 1, 2005, to September 30, 2015 (144 in the training cohort and 224 in the validation cohort) at 21 referral centers with a median follow-up of 35 months (interquartile range, 18-74 months). Data were analyzed from March 2016 to March 2018. EXPOSURES: Meta-analysis of pan-genomic studies (transcriptome, methylome, chromosome alteration, and mutational profiles) was performed on the training cohort. Targeted biomarker analysis, including targeted gene expression (BUB1B and PINK1), targeted methylation (PAX5, GSTP1, PYCARD, and PAX6), and targeted next-generation sequencing, was performed on the training and validation cohorts. MAIN OUTCOMES AND MEASURES: Disease-free survival. Cox proportional hazards regression and C indexes were used to assess the prognostic value of each model. RESULTS: Of the 368 patients (mean [SD] age, 49 [16] years), 144 were in the training cohort (100 [69.4%] female) and 224 were in the validation cohort (142 [63.4%] female). In the training cohort, pan-genomic measures classified ACC into 3 molecular groups (A1, A2, and A3-B), with 5-year survival of 9% for group A1, 45% for group A2, and 82% for group A3-B (log-rank P < .001). Molecular class was an independent prognostic factor of recurrence in stage I to III ACC after complete surgery (hazard ratio, 55.91; 95% CI, 8.55-365.40; P < .001). The combination of European Network for the Study of Adrenal Tumors (ENSAT) stage, tumor proliferation index, and molecular class provided the most discriminant prognostic model (C index, 0.88). In the validation cohort, the molecular classification, determined by targeted biomarker measures, was confirmed as an independent prognostic factor of recurrence (hazard ratio, 5.96 [95% CI, 1.81-19.58], P = .003 for the targeted classifier combining expression, methylation, and chromosome alterations; and 2.61 [95% CI, 1.31-5.19], P = .006 for the targeted classifier combining methylation, chromosome alterations, and mutational profile). The prognostic value of the molecular markers was limited for patients with stage IV ACC. CONCLUSIONS AND RELEVANCE: The findings suggest that in localized ACC, targeted classifiers may be used as independent markers of recurrence. The determination of molecular class may improve individual prognostic assessment and thus may spare unnecessary adjuvant treatment.
ABSTRACT
Pangenomic studies identified distinct molecular classes for many cancers, with major clinical applications. However, routine use requires cost-effective assays. We assessed whether targeted next-generation sequencing (NGS) could call chromosomal alterations and DNA methylation status. A training set of 77 tumors and a validation set of 449 (43 tumor types) were analyzed by targeted NGS and single-nucleotide polymorphism (SNP) arrays. Thirty-two tumors were analyzed by NGS after bisulfite conversion, and compared to methylation array or methylation-specific multiplex ligation-dependent probe amplification. Considering allelic ratios, correlation was strong between targeted NGS and SNP arrays (r = 0.88). In contrast, considering DNA copy number, for variations of one DNA copy, correlation was weaker between read counts and SNP array (r = 0.49). Thus, we generated TARGOMICs, optimized for detecting chromosome alterations by combining allelic ratios and read counts generated by targeted NGS. Sensitivity for calling normal, lost, and gained chromosomes was 89%, 72%, and 31%, respectively. Specificity was 81%, 93%, and 98%, respectively. These results were confirmed in the validation set. Finally, TARGOMICs could efficiently align and compute proportions of methylated cytosines from bisulfite-converted DNA from targeted NGS. In conclusion, beyond calling mutations, targeted NGS efficiently calls chromosome alterations and methylation status in tumors. A single run and minor design/protocol adaptations are sufficient. Optimizing targeted NGS should expand translation of genomics to clinical routine.