Genes vs Proteins: A perspective from brain tumor research

Aniruddha Mukherjee

Brain scan showing enhancing GBM tumor mass. Courtesy: RadioGraphics, Radiological Society of North America.
  The plethora of molecules inside a cell is highly regulated in terms of their abundance and functions. The regulation happens in layers which are, again, most fundamentally attributed to the expression of genes and proteins. The present article enlightens us on how a large-scale the study of proteins and genes in one of the deadliest tumors reveals layer-specific association of molecules with the time of survival of patients.

  Glioblastoma multiforme (GBM) is an aggressive form of brain tumor with incidences ranging from 1 to 5 out of 100000 people. The average survival of patients with such tumors is less than two years. Many new treatment therapies and drugs have recently shown promise; however, the caveat remains in understanding the heterogeneity of these tumors at the molecular level. Tumor heterogeneity refers to the differences in the same type of tumor across different patients that can arise due to multiple causes like the types of molecules in the tumor, time of preserving clinical samples, and the lifestyle of patients, etc. Eventually, tumor heterogeneity becomes a reason for varying responses to treatment.
A group of scientists from Tel Aviv University, Israel, have recently forged their way into GBM research showing clear demarcation between the fundamental biological molecules in terms of their ability to correlate with patient-specific characteristic features and find how proteins can distinctively inform better about certain features. One of the modern methods used by them in this work is “Proteomics, '' a broad term in research where the entire protein complement of a cell, tissue or organ is analyzed to extract information about the concerned condition. Simultaneously, they also studied the mRNA, a molecule consisting of the gene and serves as the foundation for protein synthesis inside the cell. The term coined to encompass all the mRNA molecules in a certain cell or tissue of an organism is ‘transcriptome’. Their research tells us how studying the proteome( i.e., the whole protein expressed in an organism at a certain time) inside the tumor tissues can turn out to be more suggestive of GBM patient prognosis compared to the information obtained exclusively from the genes. The intricacies in the process of protein synthesis gives rise to a higher number of total proteins which are in a constant state of interaction , hence making the proteome enormously complex and dynamic. This is likely to be a reason why proteomics by itself has become an indispensable research tool in medicine.
Image credits: Proteomics Center, Erasmus University Medical Center.

Tamar Geiger and his team of scientists, selected a cohort of 87 patients, out of which 22 were processed to study the proteome, 33 samples were used for sequencing the mRNA, while 32 were subjected to analysis at both levels of proteome and transcriptome. Here, the researchers have taken a routine approach of extracting the whole RNA or protein from the tumor tissues and subjecting those to analytical platforms to generate huge amounts of data in terms of the types, abundance and interaction of each molecule. Subsequent analysis of this information helped draw relevant conclusions about a smaller set of molecules being associated with the specific biological processes which are likely to go wrong in a tumor cell. For instance,neuron generation is one such process enriched by both proteins and genes, suggesting how there is an expansion of the formation of nerve cells or neurons contributing to the prevalence of GBM in the brain. Similarly, there are clinical parameters which consist of the data of tumor location inside the brain, patient survival after onset, tumor recurrence after treatment of patients etc. After analyzing the tumor samples, the researchers arrived at a set of significant genes and proteins and noticed that the proteins could independently show a strong association with the clinical data of patient survival on a statistical basis, whereas genes did not correlate at all. This particular analysis saw an extended version as researchers integrated both proteome and transcriptome-based data and then tried to correlate with survival bifurcated into a binary of short (less than 6 months) and long (more than 2 years) time of GBM patients. This eventually produced results of genes and proteins showing similar correlation only when compared with data from shorter survival! The researchers have clearly communicated that because their study imbibded high heterogeneity with mutations in the GBM genes, there is a future scope for extrapolating similar research with even larger cohorts of patients. Nevertheless, this study puts out multiple aberrant biological processes in GBM and shows how research targeted to specific layers of molecules can tackle the existing challenge of tumor heterogeneity to an extent that reveal the most novel molecular associations.
  1. Yanovich-Arad, Gali, Paula Ofek, Eilam Yeini, Mariya Mardamshina, Artem Danilevsky, Noam Shomron, Rachel Grossman, Ronit Satchi-Fainaro, and Tamar Geiger. “Proteogenomics of Glioblastoma Associates Molecular Patterns with Survival.” Cell Reports 34, no. 9 (March 2, 2021): 108787.

Aniruddha Mukherjee completed his BS-MS with a major in Biological Sciences from IISER Kolkata. He will be joining University of Alabama at Birmingham, U.S.A for his graduate studies in Biomedical Sciences in the coming fall. Apart from being a movie buff he enjoys cooking and playing chess.

Related Articles

please subscribe to our newsletter

signup with your email to get the latest articles instantly


Thank you for subscribing!

Please wait for a few moments while we add you to our mailing list...