## 3 Results  
Breast cancer cell lines of four different subtypes were treated by CHCP for 3 or 5 min. Following the treatment, a set of data including intracellular ROS, CA, Ki-67+ count, G1 activity, and confluence was obtained every hour for 48 h. Intracellular ROS as an oxidative stress maker was monitored, and the data are shown in Figure 1. All data plotted were subtracted by breast cancer cells stained with the fluorescent probe (CM-H2 DCFDA) but without CHCP treatment. CHCP-generated H\({}_{2}\)O\({}_{2}\) and NO\({}_{2}\)\({}^{-}\) concentrations were measured in PBS by colorimetric, and corresponding concentrations of H\({}_{2}\)O\({}_{2}\) and NO\({}_{2}\)\({}^{-}\) were added to the cells for intracellular ROS measurement as positive controls. Compared to no treatment, treatment with CHCP 120 p at both 3 and 5 min caused a significant increase in ROS levels in all breast cancer subtypes. Fluorescent intensity (Y-axis) was brought to the same scale for each cell line treated by CHCP for 3 and 5 min for easy comparison. Treatment with chemicals alone (H\({}_{2}\)O\({}_{2}\) or NO\({}_{2}\)\({}^{-}\) or in combination) also induced increased ROS levels in all four subtypes, especially at higher concentrations, but the increased intensity was much lower compared to CHCP-induced ROS. The VAR() function in R was used in conjunction with the causality() function to generate several models using the inputted data. Cell proliferation data, represented by confluence data, were defined as one \"effect\" variable, and cell death, represented by CA data, was the secondary \"effect\" variable. Tables 2 and 3 display the _p_-values and coefficients of the cell proliferation models for the 3 and 5 min CHCP treatment times, respectively, and Tables 4 and 5 display the outputs of the 3 and 5 min cell death models, respectively. Significant models yielded _p_-values under 0.05, the chosen critical value, after being treated with CHCP for a set amount of time. The absolute values of the coefficients of regression were also outputted from the VAR() function. These coefficients indicate the weight of causality. Only the coefficients of significant models can be accurately compared. For the 3 min CHCP treatment models with cell proliferation set as the effect variable, different variables displayed causality depending on the cell line studied. The significant causal variables and their associated coefficients can be seen in Table 2. The models that had significant Granger causal relationships were denoted as * (_p_ < 0.05). The Ki-67 model for SK-BR-3 was formulated based on data acquired after 80 p CAP treatment as opposed to 120 p because CHCP at 120 p eliminated all SK-BR-3 cells, making it technically impossible for confocal microscopy to image any cells. This condition is present within all of SK-BR-3's Ki-67 models. The absolute value of the coefficients of regression represents the weight of causality. CA was the only variable that lacked causality for the BT-474 cell line, whereas it was the only one which demonstrated causality for the MDA-MB-231 cell line. The intracellular ROS level did not display causality for cell proliferation in neither the MCF-7 nor the MDA-MB-231 cell lines but was significant in BT-474 and SK-BR-3. Based on the weighted coefficients, CA showed the greatest causality for the MCF-7 and MDA-MB-231 cell lines, while Ki-67 showed the greatest causality for the BT-474 and SK-BR-3 cell lines. Cell cycle activity data could not be collected for the SK-BR-3 cell line using the IncuCyte, and hence no models could be formed to test causality. Figure 1: Intracellular ROS measurements of breast cancer cell lines at 0–48 h post CHCP treatment. H\({}_{2}\)O\({}_{2}\) and/or NO\({}_{2}\)\({}^{-}\) were used as positive controls. All cells were treated by CHCP at 120 p for 3 and 5 min. (**A,B**) Treated MCF-7 cells. (**C,D**) Treated BT-474 cells. (**E,F**) Treated MDA-MB-231 cells. (**G,H**) Treated SK-BR-3 cells.