Researchers from the Faculdade de Medicina de Ribeirão Preto (FMRP-USP) published the study Proteomic-based stemness score measures oncogenic dedifferentiation and enables the identification of druggable targets in the journal Cell Genomics. The study was led by Professor Tathiane Maistro Malta and involved an international team of researchers from various institutions around the world.
The PROTsi
The research was developed to assess tumor aggressiveness and resulted in PROTsi (Protein-expression-based stemness index), an artificial intelligence-based algorithm capable of measuring this aggressiveness by recognizing molecular patterns in tumor samples. Professor Tathiane Malta explains: “By linking stem cell features to tumor biology, we developed an algorithm that enables the stratification of tumors with aggressive profiles and the identification of proteins that can serve as prognostic biomarkers.”
The program was designed to detect a characteristic called stemness, which refers to the ability of certain cancer cells—such as cancer stem cells — to maintain properties similar to normal stem cells, including self-renewal and the potential to generate different cell types within the tumor. According to Professor Tathiane Malta, tumors whose cells have a higher stemness index tend to be more aggressive and resistant to therapy.
More than 1,300 patient samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) were analyzed, covering 11 types of tumors: breast, ovary, lung (squamous cell and adenocarcinoma), kidney, uterus, brain (pediatric and adult), head and neck, colon, and pancreas. PROTsi was validated in multiple datasets, including post-translational protein modifications, reinforcing its applicability.
Protein identification: biomarkers and therapeutic targets
The use of PROTsi also enabled researchers to identify proteins that were more highly expressed in tumor samples, which can be used both as biomarkers for identifying aggressive tumors and assessing tumor aggressiveness, and as therapeutic targets. Professor Tathiane Malta notes: “Once validated, these biomarkers can assist in clinical decision-making and in managing cancer patients. Furthermore, many of these proteins represent potential targets for new therapeutic strategies, contributing to more effective anti-tumor treatments.”
Some of these proteins were already known and targeted by existing drugs, but many had not yet been described in the context of oncology, opening the door to developing new therapies.
The researchers plan to test other tumor samples to verify whether these proteins are present and to explore strategies to block these molecules, aiming to reduce tumor aggressiveness. If future studies confirm the effectiveness of this approach, clinicians could use this information to select treatments more suited to each tumor’s aggressiveness, avoiding ineffective therapies and personalizing care for each patient.
It is important to emphasize that the technology still requires further validation and is currently a research tool rather than a clinical test. This is because PROTsi analyzes all proteins in the samples, which would be unfeasible for routine patient testing. Therefore, the goal is to identify the most highly expressed proteins so that they can become biomarkers that are easier to detect.
Finally, Professor Tathiane Malta highlights PROTsi’s potential to support further research: “In addition to identifying new biomarkers and potential therapeutic targets, including targets shared across different tumor types, this work also serves as a rich data source that can be explored by the scientific community to investigate specific questions far beyond what we present here.”
Watch Professor Tathiane Malta’s explanation of the study in a video produced by Hemocentro Ribeirão Preto (automatic subtitles available):
