Drug sensitivity markers for your compound can be investigated using the response parameters of cancer cell line profiling, without the need for additional experiments. For instance, we perform analysis on IC₅₀ values and gene mutation analysis to identify genomic drug response biomarkers for cancer. Case studies have confirmed patient stratification markers that have been used in the clinic (Kooijman et al., 2022; Uitdehaag et al., 2019).

Oncolines® bioinformatics analysis can also be done for other response parameters, such as GI₅₀ or Area Under the Curve (AUC). The analysis is available for proliferation data from the Oncolines® cancer cell line panel as well as proliferation data that have been generated elsewhere.

The drug sensitivity of cancer cell lines is correlated to the cancer gene mutation status of the cell lines, yielding novel candidate drug sensitivity biomarkers (Uitdehaag et al., 2019). These biomarkers are used as selection markers for patient stratification (Zaman et al., 2017).

This analysis indicates whether anti cancer drugs or drug candidates show preferential activity in a certain cancer tissue type. 

Drug sensitivity data is coupled to gene expression data. It uses large datasets of gene expression to identify interconnections between sensitivity and resistance to your anti cancer drug and gene transcription (Uitdehaag et al., 2019).

The drug sensitivity fingerprint of compounds in Oncolines® is used for comparative analyses with other anti-cancer agents (Uitdehaag et al., 2016) and mechanism-of-action studies (Libouban et al., 2017).

We can use your internal cancer cell line proliferation data or Oncolines® proliferation results