ABSTRACT
The emergence of a huge volume of "omics" data enables a computational approach to the investigation of the biology of cancer. The cancer informatics approach is a useful supplement to the traditional experimental approach. I reviewed several reports that used a bioinformatics approach to analyze the associations among aging, stem cells, and cancer by microarray gene expression profiling. The high expression of aging- or human embryonic stem cell-related molecules in cancer suggests that certain important mechanisms are commonly underlying aging, stem cells, and cancer. These mechanisms are involved in cell cycle regulation, metabolic process, DNA damage response, apoptosis, p53 signaling pathway, immune/inflammatory response, and other processes, suggesting that cancer is a developmental and evolutional disease that is strongly related to aging. Moreover, these mechanisms demonstrate that the initiation, proliferation, and metastasis of cancer are associated with the deregulation of stem cells. These findings provide insights into the biology of cancer. Certainly, the findings that are obtained by the informatics approach should be justified by experimental validation. This review also noted that next-generation sequencing data provide enriched sources for cancer informatics study.
Subject(s)
Humans , Aging , Genetics , Metabolism , Apoptosis , Biomarkers, Tumor , Metabolism , Cell Proliferation , Computational Biology , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Microarray Analysis , Neoplasms , Genetics , Metabolism , Pathology , Neoplastic Stem Cells , PathologyABSTRACT
OBJECTIVE@#To study the expression and significance of hMSH2 protein in laryngeal squamous cell carcinoma.@*METHOD@#The expression of hMSH2 protein were detected by immunohistochemistry SP method in 51 cases of laryngeal squamous cell carcinoma, the control group included 30 cases of atypical hyperplasia tissue of vocal fold and 16 cases of normal laryngeal tissue.@*RESULT@#The expression rates of hMSH2 in laryngeal squamous cell carcinoma, atypical hyperplasia tissue of vocal fold and normal laryngeal tissue were 58.8%, 73.3%, 87.5% respectively. There was significant difference among them (P 0.05), but the expression was related with metastasis of lymph node and differentiation level (P < 0.05).@*CONCLUSION@#The deletion of hMSH2 maybe participate the early occurrence of laryngeal carcinoma; hMSH2 protein maybe delay and suppress oncogenesis and development of laryngeal carcinoma.
Subject(s)
Humans , Carcinoma, Squamous Cell , Metabolism , Pathology , Case-Control Studies , Head and Neck Neoplasms , Metabolism , Pathology , Hyperplasia , Immunohistochemistry , Laryngeal Neoplasms , Metabolism , Pathology , MutS Homolog 2 Protein , Metabolism , Squamous Cell Carcinoma of Head and NeckABSTRACT
Objective To examine the differences in the structure of brain white matter among deficit schizophrenia, nondeficit schizophrenia and healthy controls by using voxel-based morphometry (VBM). Methods Ten deficit schizophrenic patients, eleven nondeficit patients and fifteen healthy comparison subjects participated in the study. All the subjects were scanned by GE Twin Speed 1.5T MRI system. Whole brain, voxel-wise analyses of regional white matter volume were conducted by the VBM toolbox on the Matlab7.6 and SPM5. t -test was then used for the comparison between groups. Results Compared to the healthy controls, nondeficit schizophrenic patients significantly decreased the density of gray matter in the frontal, parietal, temporal, occipital lobe and basal ganglia , while the deficit patients showed the characteristically broad and significant decreasion in the frontal lobe, including left medial frontal gyrus, bilateral inferior frontal gyrus, left middle frontal gyrus, and left orbital gyrus (Cluster ≥ 30 mm3, P<0.01). Moreover, deficit patients showed the decreasion in the temporal cortex and the limbic lobe (right insula). Relative to the nondeficit schizophrenic patients, deficit patients had significant regional gray matter decreases in the left medial frontal gyrus, bilateral inferior frontal gyrus, right precentral gyrus, and right superior temporal gyrus (Cluster ≥ 30 mm3, P<0.01). Conclusion Structural heterogeneity in schizophrenia may relate to specific patterns of gray matter density reductions in deficit and nondeficit patient. However the two subtype of schizophremia patients share a common prefrontal-temperal pattern of structural brain alterations.