Making use of data of gene alterations (deletions and amplifications) mapped to the chromosomes of patients with brain tumors (Glioblastoma), this visualization is meant to give a glimpse into the complexity of gene changes that occur as the animation cycles through each patient — and hopefully also leave an impression of the huge efforts that are being done to understand this devastating disease for improved treatment.
It is rare that the broad public gets a look into the actual data that are being produced by the biomedical community. This is one attempt to show some of the thousands of gene alterations in one particular brain cancer, Glioblastoma – one of several cancers that are under intense investigation through large cross-institutional efforts, such as The Cancer Genome Atlas (TCGA). Using publicly available data of thousands of gene alterations in more than 200 Glioblastoma samples (cBio Cancer Genomics Portal), each alteration is color coded (red=amplification, blue=deletion) and mapped to the more than 20,000 annotated genes in the human genome.
As the animation cycles through each patient, it can be seen that the majority of alterations are unique to each patient, since blue and red dots appear and reappear in different places throughout the genome. This shows the complexity of this disease, which is not simply defined by a single alteration such as many inherited diseases are. It is difficult to determine if such seemingly random events are causally implicated in the disease or are secondary effects due to other factors – an area of ongoing research for scientist around the world.
We also see that there are a few hotspots that start to dominate as more patients are covered: alterations that reoccur increment in size and hereby underline some of the few high frequency alterations that characterize this disease. For example, the EGFR gene on chromosome 7 is amplified in around 40% of patients.
Glioblastoma is a devastating disease both for the patients and their families and it often affects young individuals. Hopefully recent technological developments combined with large scale efforts such as the TCGA project, will shed more light into the mechanisms driving this disease and ultimately improve treatment for patients.
Disclaimer: Although genes and alterations are accurately mapped to their locations on the chromosomes, this visualization is not meant as a objective scientific report, but is rather a freely interpreted representation of the data. For a scientific analysis of the genomic characterization of Glioblastoma, please visit here: link.
Analysis details: DNA copy number variation (CNV) data was obtained from the cancer database cBio Cancer Genomics Portal , hosted by Memorial Sloan-Kettering Cancer Center (link). The data was preprocessed with the RAE algorithm providing gene-based CNV scores and chromosomal coordinates. For simplicity only high level amplifications and homozygous deletions were used.