The author analyzed Cancer Genome Atlas (TCGA) data on 456 tumor samples that received no radiotherapy or additional pharmacotherapy. Subtypes with different survival rates were identified using the k-means method to group samples into subgroups with similar characteristics. For gene clustering, Puzanov selected 2,000 genes with highly variable expression patterns in ccRCC.

Gene expression is the process by which a gene is read and then copied to produce a messenger RNA (mRNA) that is used to synthesize proteins.

The bioinformatics algorithm was run 100 times, each time sorting the tumor samples based on the similarity of the expression patterns of 2,000 genes. Three groups (subtypes) with different survival rates were identified. The group with the lowest survival rates was associated with metastases and the worst response to subsequent treatment.


The research was conducted in several stages. In the first step, the characteristics of each cluster were examined to better understand the genetic factors that may influence the course of the disease. The author of the study then identified key genes characteristic of the high and low survival groups and constructed a network of interactions for the proteins whose synthesis is encoded by these genes.

Genetics of Kidney Cancer

Puzanov’s analysis determined which genes encoded the proteins with the most network connections. The cluster with the poorest survival rates was found to be associated with insulin-like growth factor (a protein similar in structure to insulin) and the MFI2, CP, APOB and ENAM genes known to be involved in post-translational processes. modification of proteins. In addition, genes encoding fibrinogen and prothrombin associated with blood coagulation were subtype-specific (FGA, FGG, and F2).

“Some of these key genes may affect the efficacy of antitumor treatments. For example, increased activity of CP, FGA, and FGG genes is associated with a poor response to nivolumab, and high expression of APOB and ENAM predicts a lack of response to sunitinib. This knowledge is most important for patients with malignancies. can help to determine suitable targeted treatments” – Grigory Puzanov, scientific worker of the International Bioinformatics Laboratory, Faculty of Computer Sciences of HSE University.

According to the researcher, the combined use of traditional anti-tumor agents and anticoagulants (drugs that prevent blood clotting) may increase the effectiveness of cancer treatment.

Source: Eurekalert

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