A novel anti-melanoma SRC-family kinase inhibitor

The major drawback of melanoma therapy with BRAF and MAPK inhibitors is the innate and acquired drug resistance. We therefore explored alternative targets and developed a new compound, SAB298, that is a SRC-family kinase (SFK) inhibitor. The drug is cytotoxic to patient-derived melanoma cells regardless of oncogene expression and inhibits tumor growth in vivo. As expected, it inhibited SRC and PI3K activity, and had the additional property of ERBB2 inhibition, that lead to inactivation of the two ERK phosphatases PP2A and SHP2. In 57% of the melanoma cell lines tested, the consequent increase in ERK activity lead to proteolytic degradation of its substrate, the lineage specific transcription factor MITF, likely contributing to growth arrest. Treatment with a combination of SAB298 and AZD6244 (selumetinib), induced a synergistic growth inhibition, suggesting that the new compound could be used in the clinic as a substitute for, or in combination with MAPK inhibitors.


Supplementary
GI 50 is the concentration of the drug causing 50% growth inhibition; LC 50 is the cytotoxic concentration due to 50% reduction in measured protein; and TI is LC 50 /GI 50 .

Statistical method for synergistic effects of drug combination
We used the median-effect equation derived from the mass-action law principle [1,2] to quantify the drug combination effect. Given a set of measurements representing the dose-effect of a drug, we can characterize this relationship by fitting the median-effect equation (see Eq. 1) to the measurements to estimate two parameters: 1) D m , which represents the required dose to achieve the median effect (i.e. equivalent to IC 50 , ED 50 ) and 2) m, which represents the slope of the regression line fitted to the measurements when they are plotted using log f a f a 1 −       as y-axis and log(D) as x-axis. The slope m determines the shape of the dose-effect curve which can be hyperbolic when m = 1, sigmoidal for m > 1 and negative sigmoidal when m < 1 [3]. The variables f a and D represent the effect of the drug on a scale from 0 to 1 and the drug dosage respectively.  To determine the combined effect of two drugs (D) 1 and (D) 2 , we compute the combination index (CI) based on the median-effect equation, which quantifies the degree of drug interaction where CI <1 refers to synergistic relation, CI = 1 additive relation, and CI > 1 antagonistic relation [2]. Generally, two cases are considered when studying the combined effect of two drugs: 1) the first case is when both drugs are considered mutually exclusive, and 2) the second when they are mutually non-exclusive.

Case 1: Two drugs are mutually exclusive
When two drugs are considered mutually exclusive, the combined effect or their CI value can be computed using where (D x ) 1 refers to computed dosage of the first drug (D) 1 for fractional effect (i.e. for predefined effect level f a ). Similarly, where (D x ) 2 refers to computed dosage of the second drug (D) 2 for x fractional effect (i.e. for predefined effect level f a ).

Case 2: Two drugs are mutually non-exclusive
When two drugs are considered mutually nonexclusive, the combined effect or their CI value can be computed using Equation 4 As it can be noted the difference between Equations 3 and 4 is the added multiplicative term To measure the effect of the drug in an experiment, we first average the experimental numbers across the three trials at T72 (i.e. after 72 hours). Then at each dose level, we take the ratio of the counts corresponding to a particular drug level over the counts in the control (i.e. no drug condition). We then transformed the ratios to a scale from 0 to 1, in which higher values on the transformed scale indicates lower counts in comparison to the control (no drug case). This allowed us to measure the observed effect f a for the two drugs and their combination in the three experiments.
In the case of drug combination, we had a non-constant ratio combination such that we fix the dosage of (D) 2 SAB298 and we vary the dosage of (D) 1 Selumetinib (MEKi) as before. All dose levels reported are in µM.
To measure the combined effect of the two drugs, we computed the combination index (CI) based on the medianeffect equation as described before [1,2]. We used CompuSyn [3] and we developed a Python script implementing the median-effect equations to compute CI index for the mutually exclusive case and the mutually non-exclusive case. We performed the analysis in two variations: 1) the first included all measurements of dose-effect in our experiments where 0 observed effect levels were coded as 1E-6 and 2) the second omitted measurements having observed effect levels equal to 0 (i.e. were considered as outliers). We refer to both variations in the text as Variation 1 and 2 respectively. r represents the correlation coefficient. Measurements having 0 effect were represented by 1E-6 (Variation 1).