Abstract
AIMS
Use bioinformatics methods to identify and validate associated proteins and genes in the SORL1 network. Generate a bank of patient derived cells in association with the Royal Preston Hospital BTNW tissue bank. Explore identified targets from the bioinformatics in patient derived cells.
METHOD
Proteins and genes associated with SORL1 and SORLA were identified on GeneCards. Connectivity mapping of known and predicted interactions linked to SORL1 was explored in STRING. For clinical validation differential expression was investigated by comparing genomic data from GTEX and TCGA, available at Xenabrowser. For survival analysis Kaplan-Meier curves were generated on cBioPortal. The five most differently expressed novel targets are taken forward for laboratory experiments using western blots for protein quantification and immunocytochemistry to identify and visualise target proteins.
RESULTS
A total of 73 genes (30 from GeneCards and 43 from STRING) were obtained. 63 genes from the generated SORL1-related network were shown to be differentially expressed whilst 40 were significantly different between low-surviving patients and high-surviving patients. The top five associated proteins are CKAP4, CTNND1, FN1, HSPA12A and SORCS3. CKAP4, CTNND1 and FN1 are highly expressed in both glioma and glioblastoma, but low expressed in healthy tissue. HSPA12A is low expressed in cancerous brain tissue and highly expressed in healthy samples. SORCS3 is differentially expressed in healthy samples and glioma, but significantly low expressed glioblastoma.
CONCLUSION
This project provides insight into SORL1 molecular relationships and function in tissue, cultured cells and serum from a patient cohort including demographics, disease progression and site.
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