Genome-wide loss of heterozygosity predicts aggressive, treatment-refractory behavior in pituitary neuroendocrine tumors

全基因组杂合性缺失可预测垂体神经内分泌肿瘤的侵袭性、治疗抵抗性行为

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作者:Andrew L Lin #, Vasilisa A Rudneva #, Allison L Richards #, Yanming Zhang, Hyung Jun Woo, Marc Cohen, Jamie Tisnado, Nazanin Majd, Sharon L Wardlaw, Gabrielle Page-Wilson, Soma Sengupta, Frances Chow, Bernard Goichot, Byram H Ozer, Jorg Dietrich, Lisa Nachtigall, Arati Desai, Tina Alano, Shahiba Ogi

Abstract

Pituitary neuroendocrine tumors (PitNETs) exhibiting aggressive, treatment-refractory behavior are the rare subset that progress after surgery, conventional medical therapies, and an initial course of radiation and are characterized by unrelenting growth and/or metastatic dissemination. Two groups of patients with PitNETs were sequenced: a prospective group of patients (n = 66) who consented to sequencing prior to surgery and a retrospective group (n = 26) comprised of aggressive/higher risk PitNETs. A higher mutational burden and fraction of loss of heterozygosity (LOH) was found in the aggressive, treatment-refractory PitNETs compared to the benign tumors (p = 1.3 × 10-10 and p = 8.5 × 10-9, respectively). Within the corticotroph lineage, a characteristic pattern of recurrent chromosomal LOH in 12 specific chromosomes was associated with treatment-refractoriness (occurring in 11 of 14 treatment-refractory versus 1 of 14 benign corticotroph PitNETs, p = 1.7 × 10-4). Across the cohort, a higher fraction of LOH was identified in tumors with TP53 mutations (p = 3.3 × 10-8). A machine learning approach identified loss of heterozygosity as the most predictive variable for aggressive, treatment-refractory behavior, outperforming the most common gene-level alteration, TP53, with an accuracy of 0.88 (95% CI: 0.70-0.96). Aggressive, treatment-refractory PitNETs are characterized by significant aneuploidy due to widespread chromosomal LOH, most prominently in the corticotroph tumors. This LOH predicts treatment-refractoriness with high accuracy and represents a novel biomarker for this poorly defined PitNET category.

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