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Full-Text Articles in Medicine and Health Sciences
The Distinct Metabolic Phenotype Of Lung Squamous Cell Carcinoma Defines Selective Vulnerability To Glycolytic Inhibition, Justin Goodwin, Michael L. Neugent, Shin Yup Lee, Joshua H. Choe, Hyunsung Choi, Dana M. R. Jenkins, Robin J. Ruthenborg, Maddox W. Robinson, Ji Yun Jeong, Masaki Wake, Hajime Abe, Norihiko Takeda, Hiroko Endo, Masahiro Inoue, Zhenyu Xuan, Hyuntae Yoo, Min Chen, Jung-Mo Ahn, John D. Minna, Kristi L. Helke, Pankaj K. Singh, David B. Shackelford, Jung-Whan Kim
The Distinct Metabolic Phenotype Of Lung Squamous Cell Carcinoma Defines Selective Vulnerability To Glycolytic Inhibition, Justin Goodwin, Michael L. Neugent, Shin Yup Lee, Joshua H. Choe, Hyunsung Choi, Dana M. R. Jenkins, Robin J. Ruthenborg, Maddox W. Robinson, Ji Yun Jeong, Masaki Wake, Hajime Abe, Norihiko Takeda, Hiroko Endo, Masahiro Inoue, Zhenyu Xuan, Hyuntae Yoo, Min Chen, Jung-Mo Ahn, John D. Minna, Kristi L. Helke, Pankaj K. Singh, David B. Shackelford, Jung-Whan Kim
Journal Articles: Eppley Institute
Adenocarcinoma (ADC) and squamous cell carcinoma (SqCC) are the two predominant subtypes of non-small cell lung cancer (NSCLC) and are distinct in their histological, molecular and clinical presentation. However, metabolic signatures specific to individual NSCLC subtypes remain unknown. Here, we perform an integrative analysis of human NSCLC tumour samples, patient-derived xenografts, murine model of NSCLC, NSCLC cell lines and The Cancer Genome Atlas (TCGA) and reveal a markedly elevated expression of the GLUT1 glucose transporter in lung SqCC, which augments glucose uptake and glycolytic flux. We show that a critical reliance on glycolysis renders lung SqCC vulnerable to glycolytic inhibition, …
A Heuristic Solution Of The Identifiability Problem Of The Age-Period-Cohort Analysis Of Cancer Occurrence: Lung Cancer Example., Tengiz Mdzinarishvili, Simon Sherman
A Heuristic Solution Of The Identifiability Problem Of The Age-Period-Cohort Analysis Of Cancer Occurrence: Lung Cancer Example., Tengiz Mdzinarishvili, Simon Sherman
Journal Articles: Eppley Institute
BACKGROUND: The Age-Period-Cohort (APC) analysis is aimed at estimating the following effects on disease incidence: (i) the age of the subject at the time of disease diagnosis; (ii) the time period, when the disease occurred; and (iii) the date of birth of the subject. These effects can help in evaluating the biological events leading to the disease, in estimating the influence of distinct risk factors on disease occurrence, and in the development of new strategies for disease prevention and treatment.
METHODOLOGY/PRINCIPAL FINDINGS: We developed a novel approach for estimating the APC effects on disease incidence rates in the frame of …