Researchers have achieved a breakthrough in the fight against cancer with the Pan-Cancer Proteome Atlas (TPCPA). Led by Professor of Translational OncoProteomics Connie Jimenez of Amsterdam UMC, this atlas maps nearly 10,000 proteins in approximately 1,000 tumors from 22 types of cancer. The freely accessible data offers new opportunities worldwide for finding biomarkers and therapies, and represents an important step toward better cancer care.
“Proteins control all functions in our body, and in cancer cells, protein activity is disrupted,” says Connie Jimenez about the atlas' focus on proteins. In the clinic, many of these proteins are used as targets for targeted therapy. Until now, large-scale cancer research has been based primarily on DNA research, but abnormalities at that level do not always indicate functional changes in the cell. That is why the proteins have been inventoried. Read more about the study that led to the atlas in the scientific journal Cancer Cell.
Jimenez says that thanks to the new measurement method, they are now able to map the protein profiles in 999 tumors. The atlas was created using advanced mass spectrometry. This is a special measurement technique that simultaneously determines the composition, quantity, and molecular state of the proteins in a tissue. According to Jimenez, this offers new insights into cancer biology for each individual and opportunities for developing more accurate diagnostics and tailored treatments.
New biomarkers and therapy targets
The atlas provides insight into the processes and functions of proteins, including enzymes, that play a role in 22 types of cancer. Researcher Jaco Knol explains that for each tumor type, 25 proteins have been identified that are most interesting to test in follow-up research. These include enzymes such as HERC5 (esophageal cancer) and RNF5 (liver cancer), which offer possibilities for innovative therapies that break down tumor proteins.
In addition, the researchers discovered biomarkers that can be used to divide colon tumors into four subtypes. These subtypes can then be traced back to two main groups, each with a different profile of immune cells. This offers valuable clues for predicting the prognosis of colon cancer. Furthermore, a protein signature has been developed that can help determine the tissue from which metastases originated. This is essential for the targeted treatment of patients with metastases of unknown origin.
AI model
The findings demonstrate the value of protein profiles for characterizing tumors. They also provide insight into the diversity of cancer. Through its freely accessible online data portal, TPCPA offers a searchable treasure trove of data and hypotheses for further targeted research. Earlier this year, it was announced that researchers at Stanford Medicine had succeeded in developing an AI model that predicts cancer prognosis and responses to cancer treatment.
