A clinically useful and biologically informative genomic classifier for papillary thyroid cancer.

Clinical management of papillary thyroid cancer depends on estimations of prognosis. Standard care, which relies on prognostication based on clinicopathologic features, is inaccurate. We applied a machine learning algorithm () to 502 cases annotated by The Cancer Genome Atlas Project to derive an accurate molecular prognostic classifier.

Methylation-Based Signatures for Gastroesophageal Tumor Classification.

Contention exists within the field of oncology with regards to gastroesophageal junction (GEJ) tumors, as in the past, they have been classified as gastric cancer, esophageal cancer, or a combination of both. Misclassifications of GEJ tumors ultimately influence treatment options, which may be rendered ineffective if treating for the wrong cancer attributes. It has been suggested that misclassification rates were as high as 45%, which is greater than reported for junctional cancer occurrences.