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This course covers commonly used methods in laboratory of clinical biochemistry. The teaching plan reported here is aiming for encourage students to learn the technology and methodology based on clinical needs. So the teaching plan is characterized by combination of clinical information and pathogenesis of illness with biochemical results and thus to support students' learning in an active pathway. An example is calcium concentration in circulation as a parameter to support clinical diagnosis of various illnesses.

Background: Immune microenvironment serves a vital role in glioma progression, and a large number of studies have found that tumor progression can be reduced to some extent by modulating the immune process in tumors. Materials and Methods: ImmuneScore of each sample in CGGA datasets were calculated with Estimate R package, and samples were grouped by median ImmuneScore values for differential analysis to obtain immune microenvironment differential genes. We further conducted survival analysis, ROC curve analysis, independent prognostic analysis, and clinical correlation analysis on glioma sample genes in CGGA to obtain glioma prognostic genes, and then identified their intersection with immune microenvironment DEGs by Venn tool. The GEPIA and UALCAN databases were used to verify the differential expression of intersecting genes in the glioma and normal brain and to identify our target gene. After validation of their prognostic value, we constructed a nomogram to calculate the risk score and to estimate the accuracy of prognostic model. We mined co-expression genes, enriched functions and pathways, and correlations to immune cell infiltration of unigene with an online database. Finally, we verified the differential expression of FCGBP in glioma by immunohistochemical staining. Results: We finally selected Fc fragment of IgG-binding protein (FCGBP) as our study gene. The prognostic values of FCGBP were validated by a series of analyses. Immunohistochemical staining showed that FCGBP expression increased in gliomas and was up-regulated with the progression of glioma grade. Conclusion: As a key unigene in glioma progression, FCGBP contributes to the regulation of immune microenvironment and has the potential to be a prognostic biomarker and immune targets. [ABSTRACT FROM AUTHOR]

Background: Glioma is one of the most common malignancies in the central nervous system and has limited effective therapeutic options. Therefore, we sought to identify a suitable target for immunotherapy. Materials and Methods: We screened prognostic genes for glioma in the CGGA database and GSE43378 dataset using survival analysis, receiver operating characteristic (ROC) curves, independent prognostic analysis, and clinical correlation analysis. The results were intersected with immune genes from the ImmPort database through Venn diagrams to obtain likely target genes. The target genes were validated as prognostically relevant immune genes for glioma using survival, ROC curve, independent prognostic, and clinical correlation analyses in samples from the CGGA database and GSE43378 dataset, respectively. We also constructed a nomogram using statistically significant glioma prognostic factors in the CGGA samples and verified their sensitivity and specificity with ROC curves. The functions, pathways, and co-expression-related genes for the glioma target genes were assessed using PPI networks, enrichment analysis, and correlation analysis. The correlation between target gene expression and immune cell infiltration in glioma and the relationship with the survival of glioma patients were investigated using the TIMER database. Finally, target gene expression in normal brain, low-grade glioma, and high-grade glioma tissues was detected using immunohistochemical staining. Results: We identified TNFRSF12A as the target gene. Satisfactory results from survival, ROC curve, independent prognosis, and clinical correlation analyses in the CGGA and GSE43378 samples verified that TNFRSF12A was significantly associated with the prognosis of glioma patients. A nomogram was constructed using glioma prognostic correlates, including TNFRSF12A expression, primary-recurrent-secondary (PRS) type, grade, age, chemotherapy, IDH mutation, and 1p19q co-deletion in CGGA samples with an AUC value of 0.860, which illustrated the accuracy of the prognosis prediction. The results of the TIMER analysis validated the significant correlation of TNFRSF12A with immune cell infiltration and glioma survival. The immunohistochemical staining results verified the progressive up-regulation of TNFRSF12A expression in normal brain, low-grade glioma, and high-grade glioma tissues. Conclusion: We concluded that TNFRSF12A was a viable prognostic biomarker and a potential immunotherapeutic target for glioma. [ABSTRACT FROM AUTHOR]

Summary: Lymphatic vessel density (LVD) was recently considered important for spread of several malignant tumors. However, there are no reports describing the situation in cervical carcinoma. The purpose of this study was to investigate whether LVD could serve as a risk factor for nodal metastasis and recurrence of cervical carcinoma in 147 cases of stage I patients. Other questions were if depth of invasion, proliferation rate, and tumor size could be used as predictive markers for Chinese patients with cervical carcinoma. The lymphatics were determined by immunohistochemistry with the antibody to LYVE-1, a specific lymphatic endothelium marker, and average LVD was calculated. Double immunohistochemistry and double immunofluorescence staining for LYVE-1/CD34 were used to distinguish between lymphatic and blood vessels. The results showed that average LVD in cervical carcinoma was statistically associated with inflammatory cell infiltration of carcinoma tissues, but not associated with other pathological parameters. Average LVD of the cases with nodal metastasis or recurrence was significantly higher than the cases without metastasis and recurrence in both stage IA and stage IB cervical carcinomas. The correlation between both depth of invasion and tumor size with nodal metastasis and recurrence of cervical carcinoma was also statistically significant. Ki-67 labeling index was found to be correlated with the recurrence of disease, but not to be correlated with nodal metastasis. We concluded that for the patients with stage I cervical carcinoma, increased LVD could serve as a high-risk factor for nodal metastasis and recurrence. Depth of invasion and tumor size could also be useful indicators. [Copyright &y& Elsevier]

Background: For the female population in Asia, systematic investigation on alterations of cyclin D1 in breast carcinoma is rare, and correlation between cyclin D1 expression with clinicopathological parameters, survival rate, and other prognostic marker associated with cell cycle is unclear. Methods: Expression of cyclin D1 protein, Ki-67, pRb, and p53 was determined by immunohistochemistry in 18 cases of early breast carcinomas and 80 cases of invasive ductal carcinomas. Genetic alteration of cyclin D1 gene and overexpression of cyclin D1 mRNA were detected by Southern blot and RT-PCR, respectively. Results: Expression of cyclin D1 is negative in usual ductal hyperplasia (UDH) and atypical ductal hyperplasia (ADH). However, in 52.0% (51/98) of all breast carcinomas, positive expression of cyclin D1 was observed. Five-year survival rate of the patients with positive expression of cyclin D1 (52.7%) is significantly lower than the cases with negative expression of cyclin D1 (72.1%). Positive rate of cyclin D1 protein in invasive ductal carcinoma (52.5%) is slightly higher than overexpression rate (40.8%) of cyclin D1 mRNA but significantly higher than amplification rate of cyclin D1 gene (18.4%). Expression of cyclin D1 is correlated with Ki-67 expression, but not correlated with pRb and p53 expression. Conclusions: Positive expression of cyclin D1 could serve as a poor prognostic marker for Chinese patients with breast carcinoma independent of nodal metastasis and clinical stage. Expression of cyclin D1 protein is affected more directly by overexpression of cyclin D1 mRNA rather than cyclin D1 gene amplification. The cooperation between pRb and p53 with cyclin D1 protein in the carcinogenesis of breast carcinoma is not supported by the results. [Copyright &y& Elsevier]