The algorithm is Sphinks, which can detect three groups of tumors
Many cells are usually considered “not transformed” and present close to a tumor might have already some genetic abnormalities. The novel algorithm-based method of "spatial transcriptomics," allows the possibility of identifying genetic changes in tissues that are usually considered “normal” but are close to tissues already damaged by cancer. This approach highlights the fact that many changes related to cancer development might be already present in benign tissues.
It is now feasible to integrate data generated from the analysis of tumor proteins and their alterations to pinpoint the enzymes known as kinases, responsible for the specific effects in malignant cells. These enzymes are potential targets for therapy. Sphinks (Substrate Phosphosite based inference for a network of kinases) is the name of the Artificial Intelligence (AI) algorithm in question, and it can target three different types of tumors, identify kinase proteins, and indicate a new course of action for the disease.
This method makes it feasible to predict possible changes of healthy cells and provide early diagnosis. For instance, the AI algorithms analyzing our viewing patterns of TV shows may be used to develop cancer treatment strategies.
The same mathematical approach is used to analyze big data sets, including thousands of rows of genomic data, to find recurring patterns.
The work that was recently published in the journal Nature serves as the foundation for the AI model researchers could use to determine how aggressive a cancer is, identify its weak spots, and target it with tailored therapies as the cornerstone of precision medicine.
Scientists will be able to forecast how a particular tumor will behave, similarly to how Netflix can anticipate which shows are compatible with our interests based on algorithms and past viewing decisions. We will eventually reach the stage when a physician may examine a completely sequenced tumor using AI.
The application of artificial intelligence (AI) should allow researchers to predict better how the tumor will behave based on its original genetic features. By using this AI algorithm, we can keep "one step ahead" of cancer's progression and ultimately stop it.
We have an "advantage" over cancer thanks to the use of artificial intelligence (AI technology) in oncology when compared to the analysis of tumor sequencing data for the detection of chromosomal DNA alterations.
This blog was first published in Italian for La Voce Di New York, click here to read.
Professor Antonio Giordano, M.D., Ph.D. is the Founder and Director of Sbarro Health Research Organization based at the College of Science and Technology, Temple University, Philadelphia. Connect with him on his social media channels to follow more updates: (Facebook, LinkedIn, Twitter, Instagram)