The identified emerging concepts were categorized into eight major domains -targets, therapies, interleukins, RNA-related, side effects, mechanism-based, biomarkers, and types of cancer. To visually represent these trending and emerging concepts, we constructed a trend landscape map (Fig. ) featuring a hierarchical arrangement of emerging concepts within pertinent groups and incorporated data from journal and patent publications (Fig . ). Most identified concepts ended up being clustered in the following four categories: types of i) targets, ii) therapies, iii) cancers and iv) biomarkers. The trend landscape map has been designed to provide at a glance: the average fold increase in publications over 2020-2022 and the number of publications over 2020-2022 using a color scale and symbols, respectively. Broadly speaking, the identified concepts grew at a modest (1.1 to 1.5X), fast (1.6 to 2X) or very fast (2 to >3X) pace. In addition, for the reader's ease, we have highlighted the relative growth rates of the fastest growing concepts in each of the 4 most prolific categories: types of targets, biomarkers, cancers, and therapies (see Fig. ). Both, average fold increase as well as relative growth rate are metrics indicating scientific interest albeit expressed differently with the latter being norma lized with respect to number of publications. Out of the ~100 identified emerging targets, publications for protein targets such as gasdermins, STING, cell division cycle protein 20 (CDC20), trophoblast cell-surface antigen 2 (TROP2), proprotein convertase subtilisin/kexin type 9 (PCSK9), leucocyte immunoglobulin like receptor B1 (LILRB1), and cyclin dependent kinases (CDK1 and CDK4/6 ) have doubled while those for nectin-4, 30 α-enolase 1 (ENO1), and hematopoietic progenitor kinase have nearly tripled over the last three years (2020-2022). Concepts/Areas of interest where the relative Fig. | Fastest growing concepts in a f ew selected major immuno-oncology-related categories from NLP data analysis on >350,000 publications f rom the CAS Content Collection. Data includes both journal and patent publications and expressed as relative growth rates (which are average publication rates normalized with respect to number of documents) f or the period 2020-2022. For more detail, please see Methods in Supplementary Inf ormation.