Comparative Analysis via OncolinesProfiler™ to Identify Targets and Differentiators

Helping to Bring Improved and Novel Therapies to the Right Patient Population Faster

Comparative analysis is used to find or confirm the target of your compound. The compound may be of a unique scaffold or may have emerged from phenotypical screens, in which case the biochemical target may be speculative. The intention of repurposing drugs may also trigger the need for target identification or confirmation. Clustering analysis of a broad range of anti-cancer therapeutics, using the relative potency of compounds in proliferation assays, can reveal similarities or differences in the biochemical mode of action.

Mapping Your Compound in the Competitive Field

Clustering analysis via OncolinesProfiler™ compares your compound’s IC50 fingerprint against the cellular activity of 213 anti-cancer therapeutics. The latter include standards of care, clinical stage candidates and experimental therapeutics. The anti-cancer drug list covers the wide variety of targets that is clinically applied or under investigation. Targets include tubulin, proteasome, topoisomerase, ubiquitin pathway, bromodomain, kinases, Wnt pathway, RNA synthesis, HDAC, EZH2, anti-apoptotic mechanisms and others.

  • Your compound is mapped against 213 anti-cancer agents

  • IC50 values for 102 Oncolines® cancer cell lines are used in the analysis

  • The IC50 fingerprint determines similarity to other compounds

  • Standards of care and inhibitors of novel mechanisms are included

  • Specific reference inhibitors can be added

Figure 1: Ranking 102 cancer cell lines from the Oncolines™ panel on sensitivity (pIC50) in cell proliferation assays. Cell lines expressing V600E mutant of BRAF are indicated in red; wild type in blue
Clustering tree for reversine. Reversine was originally identified in a phenotypic screen for molecules that can promote dedifferentiation of myoblasts into multipotent progenitor-like cells (Chen et al., 2007), which was attributed to its ability to inhibit Aurora B (d’Alise et al., 2008). Later, it was shown that reversine can inhibit TTK (Santaguida et al., 2008). The comparative analysis shows that reversine targets TTK (Libouban et al., 2017). Other TTK inhibitors are pictured in red.

Best-in-Class and First-in-Class Inhibitors

The target for best-in-class inhibitors is confirmed when your compound shares a cluster with the relevant targeted therapeutics. For instance, it may fall within the cluster of selective PI3K inhibitors instead of pan-PI3K inhibitors. Its best-in-class properties emerge from improved potency, increased tissue selectivity, or selectivity for a genomic biomarker.

When you are working on a novel mechanism, your compound will be unique and located separately from all other therapeutics in the database. The exact targeting will be found by, for instance, knockout experiments and zooming in on specific mechanisms via protein expression analysis.

Features of the Comparative Analysis:

  • Computational comparison to database of more than 213 anti cancer drugs

  • Unbiased analysis using Oncolines® IC50 data

  • IC50 data in the database were generated under the same conditions by Oncolines® profiling

  • Database includes profiles of common cytotoxic agents, targeted drugs, kinase inhibitors, epigenetic modulators, and investigational drugs with unique mechanisms


Kooijman et al. (2022) Comparative kinase and cancer cell panel profiling of kinase inhibitors approved for clinical use form 2018 to 2020. Frontiers in Oncology, section Cancer Molecular Targets and Therapeutics, 12:953013.

Uitdehaag et al. (2016) Cell panel profiling reveals conserved therapeutic clusters and differentiates the mechanism of action of different PI3K/mTOR, Aurora kinase and EZH2 inhibitors. Molecular Cancer Therapeutics, 15 (12):3097-3109.

Chen et al. (2007) Reversine increases the plasticity of lineage-committed mammalian cells. PNAS, 104 (25):10482-10487.

d’Alise et al. (2008) Reversine, a novel Aurora kinases inhibitor, inhibits colony formation of human acute myeloid leukemia cells. Molecular Cancer Therapeutics, 7 (5):1140-1149.

Santaguida et al. (2008) Dissecting the role of MPS1 in chromosome biorientation and the spindle checkpoint through the small molecule inhibitor reversine. Journal of Cell Biology, 190 (1):73-87.

Libouban et al. (2017) Stable aneuploid tumors cells are more sensitive to TTK inhibition than chromosomally unstable cell lines. Oncotarget, 8 (24):38309-38325.