Genomic profiling of primary and recurrent Adult Granulosa Cell Tumors of the Ovary

Adult-type granulosa cell tumor (aGCT) is a rare malignant ovarian sex cord-stromal tumor, harboring recurrent FOXL2 c.C402G/p.C134W hotspot mutations in 97% of cases. These tumors are considered to have a favorable prognosis, however aGCTs have a tendency for local spread and late recurrences, which are associated with poor survival rates. We sought to determine the genetic alterations associated with aGCT disease progression. We subjected primary non-recurrent aGCTs (n = 7), primary aGCTs that subsequently recurred (n = 9) and their matched recurrences (n = 9), and aGCT recurrences without matched primary tumors (n = 10) to targeted massively parallel sequencing of ≥410 cancer-related genes. In addition, three primary non-recurrent aGCTs and nine aGCT recurrences were subjected to FOXL2 and TERT promoter Sanger sequencing analysis. All aGCTs harbored the FOXL2 C134W hotspot mutation. TERT promoter mutations were found to be significantly more frequent in recurrent (18/28, 64%) than primary aGCTs (5/19, 26%, p = 0.017). In addition, mutations affecting TP53, MED12, and TET2 were restricted to aGCT recurrences. Pathway annotation of altered genes demonstrated that aGCT recurrences displayed an enrichment for genetic alterations affecting cell cycle pathway-related genes. Analysis of paired primary and recurrent aGCTs revealed that TERT promoter mutations were either present in both primary tumors and matched recurrences or were restricted to the recurrence and absent in the respective primary aGCT. Clonal composition analysis of these paired samples further revealed that aGCTs display intra-tumor genetic heterogeneity and harbor multiple clones at diagnosis and relapse. We observed that in a subset of cases, recurrences acquired additional genetic alterations not present in primary aGCTs, including TERT, MED12, and TP53 mutations and CDKN2A/B homozygous deletions. Albeit harboring relatively simple genomes, our data provide evidence to suggest that aGCTs are genetically heterogeneous tumors and that TERT promoter mutations and/or genetic alterations affecting other cell cycle-related genes may be associated with disease progression and recurrences

Machine learning-based prediction of microsatellite instability and high tumor mutation burden from contrast-enhanced computed tomography in endometrial cancers

Abstract To evaluate whether radiomic features from contrast-enhanced computed tomography (CE-CT) can identify DNA mismatch repair deficient (MMR-D) and/or tumor mutational burden-high (TMB-H) endometrial cancers (ECs). Patients who underwent targeted massively parallel sequencing of primary ECs between 2014 and 2018 and preoperative CE-CT were included (n = 150). Molecular subtypes of EC were assigned using DNA polymerase epsilon (POLE) hotspot mutations and immunohistochemistry-based p53 and MMR protein expression. TMB was derived from sequencing, with > 15.5 mutations-per-megabase as a cut-point to define TMB-H tumors. After radiomic feature extraction and selection, radiomic features and clinical variables were processed with the recursive feature elimination random forest classifier. Classification models constructed using the training dataset (n = 105) were then validated on the holdout test dataset (n = 45). Integrated radiomic-clinical classification distinguished MMR-D from copy number (CN)-low-like and CN-high-like ECs with an area under the receiver operating characteristic curve (AUROC) of 0.78 (95% CI 0.58–0.91). The model further differentiated TMB-H from TMB-low (TMB-L) tumors with an AUROC of 0.87 (95% CI 0.73–0.95). Peritumoral-rim radiomic features were most relevant to both classifications (p ≤ 0.044). Radiomic analysis achieved moderate accuracy in identifying MMR-D and TMB-H ECs directly from CE-CT. Radiomics may provide an adjunct tool to molecular profiling, especially given its potential advantage in the setting of intratumor heterogeneity