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A new study has identified genes associated with the most aggressive kidney cancers

A new study has identified genes associated with the most aggressive kidney cancers

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Cancer cells divide

Clear cell renal carcinoma (CCRC) is a type of kidney cancer characterized by the presence of clear cells in the tumors. It is the most common form of kidney cancer in adults, accounting for about 70-80% of all kidney cancers. CCRC tends to grow and spread quickly, and it’s often diagnosed at later stages when it has already spread to other parts of the body.

Researchers have discovered that certain cancer cells express genes responsible for blood clotting that could potentially be targeted with anticoagulants used in cancer treatments.

HSE researchers have discovered genes specific to the most aggressive subtype of clear cell kidney cancer. Grigory Puzanov, a research fellow at the International Bioinformatics Laboratory of the HSE Faculty of Informatics, analyzed data from 456 patients with the disease and identified cancer subtypes that had either a favorable or an unfavorable prognosis. The results were published in the journal Scientific Reports.

Clear cell renal carcinoma (ccRCC) is the most common form of kidney cancer. In recent decades, the number of new cases has increased. Although there is a considerable amount of data on this disease, there is still a lack of information about specific human genes that could help predict its clinical course.

Findings from Puzanov’s study show which ccRCC subtypes are more dangerous than others and which human genes appear to be responsible for disease progression. This new information is important for early detection of aggressive tumors and for designing personalized treatment plans for ccRCC patients.

The author analyzed data from the Cancer Genome Atlas (TCGA) from 456 tumor samples that did not receive radiotherapy or adjunctive 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 copied to produce a messenger RNA (mRNA), which is then used to synthesize proteins.

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

The study was carried out in several stages. In stage one, the characteristics of each cluster were examined to better understand genetic factors that might influence disease progression. The study author then identified the key genes specific to high- and low-survival clusters and constructed a network of interactions for proteins whose synthesis these genes encode.

Puzanov’s analysis identified which genes encoded proteins with the highest number of network connections. The cluster with the lowest survival rates was found to be associated with the genes MFI2, CP, APOB, and ENAM, which are known to be involved in the transport of insulin-like growth factor (a protein similar in structure to insulin) and in the Posttranslation involves modification of proteins. In addition, the genes encoding fibrinogen and prothrombin associated with blood clotting (FGA, FGG, and F2) were specific to the low-survival subtype.

“Some of these key genes can influence the effectiveness of anti-cancer therapies. For example, increased activity of the CP, FGA, and FGG genes is associated with a poor response to nivolumab, and high expression of APOB and ENAM predicts a poor response to sunitinib. This knowledge can aid in prescribing the most appropriate targeted treatments for patients with malignancy” – Grigory Puzanov, Research Fellow, International Laboratory of Bioinformatics, Faculty of Computer Science, HSE University

According to the researcher, the combined use of conventional antitumor drugs and anticoagulants (drugs that help prevent blood clots) can increase the effectiveness of cancer treatment. Thus, there is evidence that heparin, which is commonly used to treat thromboembolic events in cancer patients, contributes to patient survival and has an anti-metastatic effect.

Reference: “Identification of key ccRCC subtype genes with poor prognosis” by Grigory Andreevich Puzanov, August 26, 2022, Scientific Reports.
DOI: 10.1038/s41598-022-18620-y

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