OBJECTIVE: HER2 negative carcinomas of the breast pose a challenge for treatment due to redundancies in potential drug targets and poor patient outcomes. Our aim was to investigate the role of L-type amino acid transporter - LAT1 as a potential prognosticator and a drug target. METHODS: In this retrospective work, we have studied the expression of LAT1 in 145 breast cancer tissues via immunohistochemistry. Overall survival analysis was used to evaluate patient outcome in various groups of our cohort. RESULTS: Positive LAT1 expression was found in 27 (84.4%) luminal A subtype, 27 (64.3%) luminal B/triple positive subtype, 29 (82.9%) triple negative subtype, and 24 (66.7%) HER2-only positive subtype (p=0.1). Interestingly, negative correlation was found between LAT1 and HER2; where positive expression of LAT1 was found in 56 (83.6%) cases in negative HER2 group and 51 (65.4%) cases from positive HER2 group (p=0.01). Unfortunately, we were unable to report significant survival differences when LAT1 expression was studied in the negative HER2 group. Nevertheless, five incidents of mortality (out of 55) were reported in LAT1+/HER2- group compared to none in the LAT1-/HER2- group (N=11). CONCLUSION: Our findings of overexpression of LAT1 in negative HER2 group suggest a role of this protein as prognosticator and drug target in a challenging therapeutic cohort.
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• Keywords
• HER2, LAT1, SLC7A5, breast cancer,
• MeSH
• Adult MeSH
• Carcinoma, Ductal, Breast metabolism   pathology   surgery   MeSH
• Neoplasm Invasiveness MeSH
• Middle Aged MeSH
• Humans MeSH
• Carcinoma, Lobular metabolism   pathology   surgery   MeSH
• Neoplasm Recurrence, Local metabolism   pathology   surgery   MeSH
• Lymphatic Metastasis MeSH
• Survival Rate MeSH
• Biomarkers, Tumor metabolism   MeSH
• Follow-Up Studies MeSH
• Large Neutral Amino Acid-Transporter 1 metabolism   MeSH
• Prognosis MeSH
• Receptor, ErbB-2 metabolism   MeSH
• Receptors, Estrogen metabolism   MeSH
• Receptors, Progesterone metabolism   MeSH
• Gene Expression Regulation, Neoplastic MeSH
• Retrospective Studies MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Triple Negative Breast Neoplasms metabolism   pathology   surgery   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• ERBB2 protein, human MeSH Browser
• Biomarkers, Tumor MeSH
• Large Neutral Amino Acid-Transporter 1 MeSH
• Receptor, ErbB-2 MeSH
• Receptors, Estrogen MeSH
• Receptors, Progesterone MeSH
• SLC7A5 protein, human MeSH Browser

The purpose of this quick guide is to help new modelers who have little or no background in comparative modeling yet are keen to produce high-resolution protein 3D structures for their study by following systematic good modeling practices, using affordable personal computers or online computational resources. Through the available experimental 3D-structure repositories, the modeler should be able to access and use the atomic coordinates for building homology models. We also aim to provide the modeler with a rationale behind making a simple list of atomic coordinates suitable for computational analysis abiding to principles of physics (e.g., molecular mechanics). Keeping that objective in mind, these quick tips cover the process of homology modeling and some postmodeling computations such as molecular docking and molecular dynamics (MD). A brief section was left for modeling nonprotein molecules, and a short case study of homology modeling is discussed.

• MeSH
• Algorithms MeSH
• Amino Acids chemistry   MeSH
• Models, Biological MeSH
• Databases, Protein MeSH
• Internet MeSH
• Ions MeSH
• Hydrogen-Ion Concentration MeSH
• Ligands MeSH
• Computer Simulation MeSH
• Protein Processing, Post-Translational MeSH
• Proteins chemistry   MeSH
• Solvents MeSH
• Protein Folding MeSH
• Molecular Dynamics Simulation MeSH
• Molecular Docking Simulation MeSH
• Software MeSH
• Machine Learning MeSH
• Structural Homology, Protein MeSH
• Water MeSH
• Computational Biology methods   MeSH
• Imaging, Three-Dimensional methods   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Amino Acids MeSH
• Ions MeSH
• Ligands MeSH
• Proteins MeSH
• Solvents MeSH
• Water MeSH

Some therapeutic side-effects result from simultaneous activation of homolog receptors by the same ligand. Tropomyosin receptor kinases (TrkA, TrkB and TrkC) play a major role in the development and biology of neurons through neurotrophin signaling. The wide range of cross-interactions between Trk receptors and neurotrophins vary in selectivity, affinity and function. In this study, we discuss new perspectives to the manipulation of side-effects via a better understanding of the cross-interactions at the molecular level, derived by computational methods. Available crystal structures of Trk receptors and neurotrophins are a valuable resource for exploitation via molecular mechanics (MM) and dynamics (MD). The study of the energetics and dynamics of neurotrophins or neurotrophic peptides interacting with Trk receptors will provide insight to structural regions that may be candidates for drug targeting and signaling pathway selection.

• Keywords
• drug side-effect, molecular dynamics, molecular mechanics, neurotrophic tyrosine kinase receptor, neurotrophin, tropomyosin receptor kinase,
• Publication type
• Journal Article MeSH