OBJECTIVE: To evaluate head and neck squamous cell carcinomas (HNSCCs) for differences in protein expression between oral cavity, oropharynx, larynx, and hypopharynx subsites. DESIGN: Retrospective proteomic analysis using tissue microarray (TMA) and 2-dimensional difference gel electrophoresis (2D-DIGE). For the TMA, automated quantitative protein expression analysis was used to interrogate levels of 4 cell-cycle regulatory proteins chosen for their known roles in cancer (cyclin D1, p53, Rb, and p14). For the 2D-DIGE, lesional and normal adjacent tissues were enriched by laser capture microdissection. Total protein was extracted, analyzed by 2D-DIGE with saturation dye labeling, and evaluated for relative abundance levels of individual protein spots. SETTING: Two tertiary-care academic medical centers. PATIENTS: Seventy-one patients with HNSCC for TMA, and 14 patients with HNSCC with frozen tumor and normal tissue for 2D-DIGE. RESULTS: The automated quantitative analysis of protein expression analysis revealed no difference between subsite for cyclin D1, p53, Rb, or p14 expression. The 2D-DIGE study was based on 28 gels (14 cancer gels and 14 adjacent normal gels), and 732 spots were identified as matching across more than 90% of gels. Significance was evaluated based on false discovery rate (FDR) estimated from permuted data sets. There were no significant differences in protein expression between subsites (FDR greater than or equal to 30% in all instances). CONCLUSIONS: Observed differences in outcomes between HNSCCs from different subsites may not reflect differences in tumor biologic characteristics between subsites. Rather, it is possible that observed clinical heterogeneity among HNSCCs may be based on other factors, such as viral vs chemical carcinogenesis.
OBJECTIVE: To evaluate head and neck squamous cell carcinomas (HNSCCs) for differences in protein expression between oral cavity, oropharynx, larynx, and hypopharynx subsites. DESIGN: Retrospective proteomic analysis using tissue microarray (TMA) and 2-dimensional difference gel electrophoresis (2D-DIGE). For the TMA, automated quantitative protein expression analysis was used to interrogate levels of 4 cell-cycle regulatory proteins chosen for their known roles in cancer (cyclin D1, p53, Rb, and p14). For the 2D-DIGE, lesional and normal adjacent tissues were enriched by laser capture microdissection. Total protein was extracted, analyzed by 2D-DIGE with saturation dye labeling, and evaluated for relative abundance levels of individual protein spots. SETTING: Two tertiary-care academic medical centers. PATIENTS: Seventy-one patients with HNSCC for TMA, and 14 patients with HNSCC with frozen tumor and normal tissue for 2D-DIGE. RESULTS: The automated quantitative analysis of protein expression analysis revealed no difference between subsite for cyclin D1, p53, Rb, or p14 expression. The 2D-DIGE study was based on 28 gels (14 cancer gels and 14 adjacent normal gels), and 732 spots were identified as matching across more than 90% of gels. Significance was evaluated based on false discovery rate (FDR) estimated from permuted data sets. There were no significant differences in protein expression between subsites (FDR greater than or equal to 30% in all instances). CONCLUSIONS: Observed differences in outcomes between HNSCCs from different subsites may not reflect differences in tumor biologic characteristics between subsites. Rather, it is possible that observed clinical heterogeneity among HNSCCs may be based on other factors, such as viral vs chemical carcinogenesis.
Authors: Qiang Huang; Guo Pei Yu; Steven A McCormick; Juan Mo; Bhakti Datta; Manoj Mahimkar; Philip Lazarus; Alejandro A Schäffer; Richard Desper; Stimson P Schantz Journal: Genes Chromosomes Cancer Date: 2002-06 Impact factor: 5.006
Authors: Naila Cannes do Nascimento; Andrea Pires Dos Santos; Rodrigo Mohallem; Uma K Aryal; Jun Xie; Abigail Cox; M Preeti Sivasankar Journal: J Proteomics Date: 2021-11-23 Impact factor: 4.044
Authors: Andrew J Bowen; Dale C Ekbom; Danielle Hunter; Stephen Voss; Kathleen Bartemes; Andrew Mearns-Spragg; Michael S Oldenburg; Serban San-Marina Journal: Laryngoscope Investig Otolaryngol Date: 2022-09-24
Authors: Mark A Merkley; Paul M Weinberger; Lana L Jackson; Robert H Podolsky; Jeffrey R Lee; William S Dynan Journal: Otolaryngol Head Neck Surg Date: 2009-11 Impact factor: 3.497
Authors: Ying Lin; Phillip J Buckhaults; Jeffrey R Lee; Hairong Xiong; Christopher Farrell; Robert H Podolsky; Robert R Schade; William S Dynan Journal: Neoplasia Date: 2009-09 Impact factor: 5.715
Authors: Dehuang Guo; Qinqin Xu; Sarabjot Pabla; John Koomen; Paul Biddinger; Ashok Sharma; Simarjot Pabla; Rafal Pacholczyk; Chien-Chung Chang; Kevin Friedrich; Kamran Mohammed; Robert C Smallridge; John A Copland; Jin-Xiong She; Paul M Weinberger Journal: Int J Mol Sci Date: 2018-02-14 Impact factor: 5.923