News
Genomic Analysis of Uveal Melanoma Case with Good Response to Therapy
Personalized OncoGenomics case report provides insight into uveal melanoma and immune checkpoint inhibitor therapy.
Whole Genome and Transcriptome Analysis Benefits Clinical Cancer Care
A prospective study of 570 Personalized OncoGenomic (POG) patients demonstrates how whole genome and transcriptome analysis can impact cancer treatment.
Genomic Analysis of Adrenocortical Cancer Identifies Treatment Targets
Results of whole-genome and transcriptome analysis identifies two genomic targets for potential treatment of adrenocortical cancer, a rare disease with limited therapeutic options.
Evaluating whole genome transcriptome analysis for cancer biomarker discovery and diagnosis
BC Cancer researchers assess whole genome transcriptome analysis for its ability to identify genomic biomarkers and predict the tumour site or tissue of origin for various cancers.
New animation makes cancer genomics understandable for everyone
A new animated video that explains cancer genomics in simple language and relatable graphics is useful for many audiences including patients that may want to participate in the program, researchers and practitioners working in the field and those helping to educate others on the topic.
Treatment of pediatric chordoma with an immune checkpoint inhibitor slows tumour growth
A POG case report suggests there’s a molecular subset of immunologically hot, INI1-deficient pediatric chordomas and rhabdoid tumours with implications for immune checkpoint inhibitor therapy.
Pediatric case study demonstrates value in whole genome sequencing for cancer treatment planning
Whole genome sequencing allows for the identification of novel genomic alterations that are not detected by standard clinical techniques. In some cases, identification of these features can reveal therapeutic options for patients with otherwise untreatable cancers.
Molecular subtypes of common pancreatic cancers can be predicted from tumour characteristics
Gene expression analysis of pancreatic ductal adenocarcinoma (PDAC) tumours enables clinicians to stratify patients into molecular subgroups and select treatments that are best suited to each type; however, molecular subtyping remains cost-prohibitive and is not yet part of routine cancer care.
A machine learning algorithm for automated tumour sample processing
As researchers work towards establishing whole genome and transcriptome analysis into clinical practice for cancer care, scientists at the GSC continue developing innovative laboratory methods to improve efficiency and accuracy.