Mallak N, O’Brien SR, Pryma DA, Mittra E. Theranostics in neuroendocrine tumors. Cancer J. 2024;30:185.

Article  CAS  PubMed  Google Scholar 

Hallet J, Law CHL, Cukier M, Saskin R, Liu N, Singh S. Exploring the rising incidence of neuroendocrine tumors: a population-based analysis of epidemiology, metastatic presentation, and outcomes. Cancer. 2015;121:589–97.

Article  PubMed  Google Scholar 

Oberg K, Modlin IM, De Herder W, Pavel M, Klimstra D, Frilling A, et al. Consensus on biomarkers for neuroendocrine tumour disease. Lancet Oncol. 2015;16:e435–46.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Singh S, Law C. Chromogranin A: a sensitive biomarker for the detection and post-treatment monitoring of gastroenteropancreatic neuroendocrine tumors. Expert Rev Gastroenterol Hepatol. 2012;6:313–34.

Article  CAS  PubMed  Google Scholar 

Stinner B, Rothmund M. Neuroendocrine tumors (carcinoids) of the appendix. Best Pract Res Clin Gastroenterol. 2005;19:729–38.

Article  CAS  PubMed  Google Scholar 

Klöppel G. Neuroendocrine neoplasms: dichotomy, origin and classifications. Visc Med. 2017;33:324–30.

Article  PubMed  PubMed Central  Google Scholar 

Carrasquillo JA, Chen CC. Molecular imaging of neuroendocrine tumors. Semin Oncol. 2010;37:662–79.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Dahia PLM. Pheochromocytoma and paraganglioma pathogenesis: learning from genetic heterogeneity. Nature Rev Cancer. 2014;14(2):108–19.

Article  CAS  Google Scholar 

Lowery AJ, Walsh S, McDermott EW, Prichard RS. Molecular and therapeutic advances in the diagnosis and management of malignant pheochromocytomas and paragangliomas. Oncologist. 2013;18:391–407.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lefebvre M, Foulkes WD. Pheochromocytoma and paraganglioma syndromes: genetics and management update. Curr Oncol. 2014;21:e8-17.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kantorovich V, Eisenhofer G, Pacak K. Pheochromocytoma: an endocrine stress mimicking disorder. Ann N Y Acad Sci. 2008;1148:462–8.

Article  PubMed  PubMed Central  Google Scholar 

Manger WM, Eisenhofer G. Pheochromocytoma: diagnosis and management update. Curr Sci Inc. 2004;6:477–84.

Article  Google Scholar 

Burnichon N, Laure V, Laurence A, Rossella L, de Reynies A, Annabelle V, Elodie J, et al. Integrative genomic analysis reveals somatic mutations in pheochromocytoma and paraganglioma. Hum Mol Genet. 2011;20(20):3974–85.

Article  CAS  PubMed  Google Scholar 

Insinga A, Cicalese A, Faretta M, Gallo B, Albano L, Ronzoni S, et al. DNA damage in stem cells activates p21, inhibits p53, and induces symmetric self-renewing divisions. Proc Natl Acad Sci U S A. 2013;110:3931–6.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yin Y, Shen WH. PTEN: a new guardian of the genome. Oncogene. 2008;27:5443–53.

Article  CAS  PubMed  Google Scholar 

Mantovani F, Collavin L, Del Sal G. Mutant p53 as a guardian of the cancer cell. Cell Death Differ. 2019;26:199–212.

Article  PubMed  Google Scholar 

Schulz-Heddergott R, Moll UM. Gain-of-function (GOF) mutant p53 as actionable therapeutic target. Cancers (Basel). 2018;10:188.

Article  PubMed  Google Scholar 

Larsson L-G. Oncogene- and tumor suppressor gene-mediated suppression of cellular senescence. Semin Cancer Biol. 2011;21:367–76.

Article  CAS  PubMed  Google Scholar 

Strong VE, Kennedy T, Al-Ahmadie H, Tang L, Coleman J, Fong Y, et al. Prognostic indicators of malignancy in adrenal pheochromocytomas: clinical, histopathologic, and cell cycle/apoptosis gene expression analysis. Surgery. 2008;143:759–68.

Article  PubMed  Google Scholar 

Smith ND, Rubenstein JN, Eggener SE, Kozlowski JM. The p53 tumor suppressor gene and nuclear protein: basic science review and relevance in the management of bladder cancer. J Urol. 2003;169:1219–28.

Article  CAS  PubMed  Google Scholar 

Galluzzi L, Kepp O, Vander Heiden MG, Kroemer G. Metabolic targets for cancer therapy. Nat Rev Drug Discov. 2013;12:829–46.

Article  CAS  PubMed  Google Scholar 

Tomczak K, Czerwińska P, Wiznerowicz M. Review the cancer genome atlas (TCGA): an immeasurable source of knowledge. Współczesna Onkologia. 2015;1A:68–77.

Article  Google Scholar 

NIH. About the GDC | NCI Genomic Data Commons [Internet]. [cited 2024 Aug 6]. Available from: https://gdc.cancer.gov/about-gdc

Cancer Genome Atlas Research Network, Weinstein JN, Collisson EA, Mills GB, Shaw KRM, Ozenberger BA, et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet. 2013;45:1113–20.

Guo Y, Dai Y, Yu H, Zhao S, Samuels DC, Shyr Y. Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis. Genomics. 2017;109:83–90.

Article  CAS  PubMed  Google Scholar 

McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome analysis toolkit: a mapreduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297–303.

Article  CAS  Google Scholar 

Craven KE, Fischer CG, Jiang L, Pallavajjala A, Lin M-T, Eshleman JR. Optimizing insertion and deletion detection using next-generation sequencing in the clinical laboratory. J Mol Diagn. 2022;24:1217–31.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, Sougnez C, et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol. 2013;31:213–9.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38: e164.

Article  PubMed  PubMed Central  Google Scholar 

McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GRS, Thormann A, et al. The ensemble variant effect predictor. Genome Biol. 2016;17:122.

Article  PubMed  PubMed Central  Google Scholar 

Ng PC. SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003;31:3812–4.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Flanagan SE, Patch A-M, Ellard S. Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations. Genet Test Mol Biomarkers. 2010;14:533–7.

Article  CAS  PubMed  Google Scholar 

Salman HA, Kalakech A, Steiti A. Random forest algorithm overview. Babylon J Mach Learn. 2024;2024:69–79.

Article  Google Scholar 

Fishbein L, Leshchiner I, Walter V, Danilova L, Robertson AG, Johnson AR, et al. Comprehensive molecular characterization of pheochromocytoma and paraganglioma. Cancer Cell. 2017;31:181–93.

Article  CAS  PubMed  PubMed Central