Diagnostic, prognostic, and therapeutic biomarkers in neuroendocrine tumors
Creators: name: Vaughn, Hayley
Publisher: name: University of Iowa
Year: 2024
Subjects: everolimus resistance
functional copy number alterations
neuroendocrine tumors
Biomarkers

description: Neuroendocrine tumors (NETs) are a heterogenous group of mainly epithelial neuroendocrine neoplasms with high metastatic potential. Up to 60% of patients have advanced metastatic liver disease at the time of diagnosis. Twelve to fifty percent of primary NETs in the abdomen are regularly missed due to small tumor size, body habitus, and abdominal gases. Of these, 50% originate in the pancreas (pNETs) and small bowel (sbNETs). Often located in close proximity, they are difficult to differentiate because of similar signs and symptoms, including abdominal pain, nausea, poor appetite, weight loss, and diarrhea. However, it is particularly important to differentiate between pNETs and sbNETs due to different treatment options and protocols.
description: Everolimus, a mammalian target of rapamycin (mTOR) inhibitor, was approved for use in pNETs after a RADIANT-3 trial reported an increase in progression free survival (PFS). Unfortunately, no increase in overall survival (OS) was observed, which alludes to acquired everolimus resistance and creates a real limit to patient therapy. In addition to everolimus resistance, up to 5% of NETs defy site of origin assignment after exhaustive immunohistochemical and radiologic evaluation. In this backdrop, the lead authors of the 2022 World Health Organization (WHO) NET Classification stated that there remains a critical need for additional biomarkers to better classify NETs. Here we identified functional copy number alterations (fCNAs) and gene mutations that may be used as (1) diagnostic, (2) prognostic, and (3) therapeutic NET biomarkers.
description: Biomarkers are any biological substance, structure, or process that can be quantified to influence or predict the outcome of a disease. fCNAs are DNA copy number changes with concordant differential gene expression, are less likely to be bystander genetic lesions, and could serve as robust and reproducible tumor biomarkers.
description: To identify candidate (1) diagnostic and (2) prognostic NET biomarkers, we identified fCNAs by integrating chromosomal microarray and RNA-seq differential gene expression data from 31 pNETs and 33 sbNETs. Tumors were resected from 47 early disease progression (&lt;24 months) and 17 late disease progression (&gt;24 months) patients. Candidate fCNAs that accurately differentiated these groups were replicated using fluorescence in situ hybridization (FISH) on formalin-fixed, paraffin-embedded (FFPE) tissues in a larger validation cohort of 60 pNETs and 82 sbNETs that consisted of 52 early and 65 late disease progression samples. Logistic regression analysis was performed to determine the predictive ability and quality performance metrics were established. Our results indicate that copy number changes at chromosomal loci 7q31.2, 9p21.3, 17q12, 18q21.2, and 19q12 may be used as diagnostic and prognostic NET biomarkers.
description: To identify candidate genes that may be used as (3) therapeutic biomarkers in everolimus resistance, we performed both spontaneous (experimental= 2, control= 3) and Sleeping beauty induced (experimental= 7, control= 10) resistant screens in BON1 cells. DNA and RNA were collected, and sequencing was performed to identify gene mutations while assessing their impact on gene expression. Our results indicate that mutations in Angiopoietin 1(ANGPT1), DAB Adaptor Protein 1 (DAB1), Dynein Axonemal Heavy Chain 12 (DNAH12), Fanconi-associated Nuclease 1 (FAN1), Genetic Suppressor Element (GSE1), Glutaminase (GLS), LINE1 Type Transposase Domain Containing 1 (L1TD1), and Synaptic Ras GTPase Activating Protein 1 (SYNGAP1) may be involved in everolimus resistance.
description: Taken together, these results provide a direct response to the 2022 WHO NET Classification that stated that there is a critical need for additional biomarkers to better classify NETs. We identified fCNAs that can be utilized as (1) diagnostic NET biomarkers to determine primary tumor site for patients with metastatic liver disease and (2) prognostic NET biomarkers to help guide risk stratification of GEP NETs. We also provide a comprehensive list of candidate genes that may contribute to everolimus resistance and serve as (3) therapeutic NET biomarkers. Overall, the thorough work of this thesis could greatly impact patient care in the future.