Iterative Internet Autonomous Agent (IIAA), is a tool we developed to help us to search within the huge ―and growing daily―, databases of research articles and papers to discover novel Tumor Markers to include in future versions of current tests, as well as in new ones we are working.
Currently, IIAA is running in an independent Cloud Cluster and compiles a huge list of several proteins believed to be differentially expressed in human cancer 24/7 from Internet literature ―at the present stage, we are only using the online National Center for Biotechnology Information (NCBI) database PubMed, but in the mid-term we will include EMBASE as well as Grey Literature searches―, with more than 1,000 already indexed. These proteins, only some of which have been detected in plasma to date, represent a population of candidate plasma biomarkers that could be useful in early cancer detection and monitoring given sufficiently sensitive specific assays.
For each of the proteins identified above, a second-level iterated search is performed using the known protein name together with the cancer name (such as “pancreas” or “pancreas cancer” for Pancreas Cancer). That means we will begin to prioritize these markers for future validation by frequency of literature citations, both total and as a function of time.
The candidates include proteins involved in “oncogenesis”, “angiogenesis”, “development”, “differentiation”, “proliferation”, “apoptosis”, “hematopoiesis”, “immune and hormonal responses”, “cell signaling”, “nucleotide function”, “hydrolysis”, “cellular homing”, “cell cycle and structure”, the “acute phase response” and “hormonal control”.
Many of them have been detected in studies of tissue or nuclear components; nevertheless we hypothesize that most ―if not all―, should be present in plasma at some level. By the way, we have noticed that of the whole candidates only a small group is approved as “tumor associated antigens” by the US Food and Drug Administration (FDA) ―something to keep in mind to accelerate the commercialization of the resulting MBDAA Tests in the United States―.
Thank to results obtained, we think this Very Large Scale Validation (VLSV) of candidate biomarkers will fill the gap currently existing between basic research and clinical use of advanced diagnostics, allowing us to develop others MBDAA Tests in less time than our OncoBREAST Dx, OncoLUNG Dx, OncoOVARIAN Dx, OncoPROSTATE Dx and OncoCUP Dx.