Hongying Hao1, Deyi Xiao1, Jianmin Pan2, Jifu Qu1, Michael Egger1, Sabine Waigel3, Mary Ann G Sanders4, Wolfgang Zacharias3,5, Shesh N Rai2, Kelly M McMasters6. 1. Department of Surgery, University of Louisville School of Medicine, Louisville, KY, USA. 2. Biostatistics Shared Facility, James Graham Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. 3. Genomics Facility, James Graham Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. 4. Department of Pathology, University of Louisville School of Medicine, Louisville, KY, USA. 5. Department of Medicine and Department of Pharmacology and Toxicology, James Graham Brown Cancer Center, University of Louisville School of Medicine, Louisville, KY, USA. 6. Department of Surgery, University of Louisville School of Medicine, Louisville, KY, USA. mcmasters@louisville.edu.
Abstract
PURPOSE: Melanoma patients with a single microscopically-positive sentinel lymph node (SLN) are classified as stage III and are often advised to undergo expensive and substantially toxic adjuvant therapy. However, the 5-year survival rate for these patients, with or without adjuvant therapy, varies from 14 to 85 %, representing a heterogeneous biological population with a variable prognosis. We aimed to identify an SLN gene signature to aid in risk stratification of patients with tumor-positive SLNs. METHODS: Microarray experiments were performed to screen SLN genes in recurrence (N = 39) versus non-recurrence (N = 58) groups in the training dataset. Quantitative reverse-transcriptase polymerase chain reaction (RT-PCR) assay was applied to confirm the expression of selected SLN genes, which were further verified using an independent validation cohort (N = 30). Area under the receiver operating characteristic curve (AUC) was calculated to evaluate prognostic accuracy of the selected SLN gene panel, and the prognostic value of our SLN gene signature was also compared with the current American Joint Committee on Cancer (AJCC) staging system. RESULTS: We identified two SLN genes (PIGR and TFAP2A) that provided high prognostic accuracy in SLN-positive melanoma patients (AUC = 0.864). These two SLN genes, along with clinicopathological features, can differentiate the high- and low-risk groups in node-positive melanoma patients in this cohort. CONCLUSION: The two SLN genes, when combined with clinicopathological features, may offer a new tool for personalized patient risk assessment.
PURPOSE:Melanomapatients with a single microscopically-positive sentinel lymph node (SLN) are classified as stage III and are often advised to undergo expensive and substantially toxic adjuvant therapy. However, the 5-year survival rate for these patients, with or without adjuvant therapy, varies from 14 to 85 %, representing a heterogeneous biological population with a variable prognosis. We aimed to identify an SLN gene signature to aid in risk stratification of patients with tumor-positive SLNs. METHODS: Microarray experiments were performed to screen SLN genes in recurrence (N = 39) versus non-recurrence (N = 58) groups in the training dataset. Quantitative reverse-transcriptase polymerase chain reaction (RT-PCR) assay was applied to confirm the expression of selected SLN genes, which were further verified using an independent validation cohort (N = 30). Area under the receiver operating characteristic curve (AUC) was calculated to evaluate prognostic accuracy of the selected SLN gene panel, and the prognostic value of our SLN gene signature was also compared with the current American Joint Committee on Cancer (AJCC) staging system. RESULTS: We identified two SLN genes (PIGR and TFAP2A) that provided high prognostic accuracy in SLN-positive melanomapatients (AUC = 0.864). These two SLN genes, along with clinicopathological features, can differentiate the high- and low-risk groups in node-positive melanomapatients in this cohort. CONCLUSION: The two SLN genes, when combined with clinicopathological features, may offer a new tool for personalized patient risk assessment.
Authors: Daniel Eiger; Daniel Arcuschin de Oliveira; Renato Leão de Oliveira; Murilo Costa Sousa; Mireille Darc Cavalcante Brandão; Renato Santos de Oliveira Filho Journal: An Bras Dermatol Date: 2018 Jul-Aug Impact factor: 1.896
Authors: Jeffrey R White; Dakota T Thompson; Kelsey E Koch; Boris S Kiriazov; Anna C Beck; Dana M van der Heide; Benjamin G Grimm; Mikhail V Kulak; Ronald J Weigel Journal: Cancer Res Date: 2021-07-01 Impact factor: 12.701
Authors: James Brierley; Brian O'Sullivan; Hisao Asamura; David Byrd; Shao Hui Huang; Anne Lee; Marion Piñeros; Malcolm Mason; Fabio Y Moraes; Wiebke Rösler; Brian Rous; Julie Torode; J Han van Krieken; Mary Gospodarowicz Journal: Nat Rev Clin Oncol Date: 2019-08-06 Impact factor: 66.675