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Proteomics May Be Used to Predict Treatment Outcomes in Triple-Negative Breast Cancer

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Key Points

  • Analysis identified the six kinases responsible for the activation pattern characteristic of the proteome of patients with triple-negative breast cancer whose disease relapses.
  • Patients in whom none of these proteins was activated had a 95% chance of being cured, or at least not suffering a relapse 12 years after treatment. However, if even one of the 6 kinases was active, the risk of relapse multiplied by 10.
  • These six kinases can be inhibited using drugs, which are already in use against some of them. With 15 treatment combinations in 10 different models—150 situations—researchers achieved a superior therapeutic effect to the sum total of the therapeutic effects of each drug separately in 99.3% of cases.

In triple-negative breast cancer, researchers have so far been unable to identify markers that can classify patients by prognosis or probability of responding to different treatments. In a study published by Zagorac et al in Nature Communications, researchers from the Spanish National Cancer Research Centre (CNIO) described a successful classification of patients with triple-negative breast cancer, which for the first time separates those who can be cured from those whose disease may recur. The study also identifies new pharmacologic targets and indicates that in patients with these targets, combined treatments with existing drugs could be effective.

Specifically, the researchers have identified six protein kinases, whose functional status predicts the evolution of triple-negative breast cancer. Furthermore, researchers have found a way for these proteins to be studied in hospitals, so that in the future, the detection of these kinases may be a regular clinical test, just as genetic profile analysis of any tumor is today.

“Until now, it has not been possible to establish a link between the presence of certain mutations in triple-negative breast cancer and a prognosis or response to drug treatment", explained oncologist Miguel Ángel Quintela, MD, PhD, Director of the Breast Cancer Clinical Research Unit at CNIO and lead author of the study. “We have shown for the first time that proteomics can be used to predict the evolution of triple-negative breast cancer and to select combinations of pairs of drugs as candidates for clinical trials.”

From Genomics to Proteomics

Decades of research into cancer genomics have identified, in many cancers, dominant gene mutations that determine the progression of the tumor and guide the design of personalized treatment pathways. But triple-negative breast cancer is caused by numerous mutations, which act in conjunction and in unique combinations for each patient. So far, it has not been possible to find dominant gene mutations that provide an indicator of prognosis or response to drug treatment.

As the researchers explained in their study report, "although studies based on genetics have provided unprecedented knowledge about breast cancer and its subtypes, in triple-negative breast cancer, this new information has revealed major heterogeneity that has prevented us, so far, from defining prognostic or predictive factors. [This fact] has meant that conventional chemotherapy is still the main therapeutic option in triple-negative breast cancer.” For that reason, “it would be extremely interesting” for this type of cancer to have a classification system associated with different therapeutic options, the authors wrote.

With this aim, CNIO researchers chose not to analyze the genes involved in triple-negative breast cancer, but rather their product: the proteins whose synthesis is ordered by those genes. Their hypothesis was that the numerous genetic alterations of patients could translate into recognizable patterns of the functional status—activation or not—of all the tumor’s proteins—its proteome.

Study Findings

In samples of tumors from 34 patients, the researchers found the biochemical marks of the activation of tumor proteins; they found more than 2 million, but with the help of sophisticated bioinformatic tools, they detected that, among all these signals, there is a precise combination that is only found in patients who relapse. These proteins are activated through kinase enzymes—which are, in turn, proteins—and so the next step was to find the kinases responsible for that specific pattern. Finally, the analysis identified the six kinases responsible for the activation pattern characteristic of the proteome of patients whose disease relapses. Some of them had been studied previously, but until now, “there was no reason to [hone] in on them,” explained Dr. Quintela.

The validation of their findings with 170 patients confirmed the value of these six kinases as a marker. Patients in whom none of these proteins was activated had a 95% chance of being cured, or at least not suffering a relapse 12 years after treatment. However, if even one of the 6 kinases was active, the risk of relapse multiplied by 10.

These six kinases can be inhibited using drugs, and there are already drugs in use against some of them. Furthermore, to prove the clinical relevance of their findings, the researchers studied xenografts derived from patients, where they explored the antitumor activity of 15 different combinations of drugs and related it with the activation profile of the 6 kinases. They found combinations that achieved “promising antitumor activity.” Specifically, with 15 combinations in 10 different models—150 situations—researchers achieved a superior therapeutic effect to the sum total of the therapeutic effects of each drug separately in 99.3% of cases.

Looking Ahead

Analysis of the functional status of proteins cannot currently be conducted as a routine test in hospitals, but the authors have translated the activation patterns of the kinases into indicators of immunohistochemistry, which can be analyzed easily in hospitals. The objective is for the study of the six kinases identified to eventually become a regular clinical test.

The researchers are now focusing on “validating these markers in other stages of diseases, standardizing kinase determinations by way of a diagnostic test, and organizing clinical trials using the therapeutic combinations described in this paper on patients with advanced disease,” said Dr. Quintela.

The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.


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