Mathematical modelling of breast cancer cells in response to endocrine therapy and Cdk4/6 inhibition.

Oestrogen receptor (ER)-positive breast cancer is responsive to a number of targeted therapies used clinically. Unfortunately, the continuous application of any targeted therapy often results in resistance to the therapy. Our ultimate goal is to use mathematical modelling to optimize alternating therapies that not only decrease proliferation but also stave off resistance. Toward this end, we measured levels of key proteins and proliferation over a 7-day time course in ER+ MCF-7 breast cancer cells. Treatments included endocrine therapy, either oestrogen deprivation, which mimics the effects of an aromatase inhibitor, or fulvestrant, an ER degrader. These data were used to calibrate a mathematical model based on key interactions between ER signalling and the cell cycle. We show that the calibrated model is capable of predicting the combination treatment of fulvestrant and oestrogen deprivation. Further, we show that we can add a new drug, palbociclib, to the model by measuring only two key proteins, cMyc and hyperphosphorylated RB1, and adjusting only parameters associated with the drug. The model is then able to predict the combination treatment of oestrogen deprivation and palbociclib. We illustrate the model's potential to explore protocols that limit proliferation and hold off resistance by not depending on any one therapy.

Detection of MYD88 L265P mutation by real-time allele-specific oligonucleotide polymerase chain reaction.

MYD88 L265P mutation has been reported in ∼90% of Waldenström's Macroglobulinemia (WM) patients and immunoglobulin M (IgM) monoclonal gammopathies of uncertain significance (MGUS), as well as in some cases of lymphoma and chronic lymphocytic leukemia. The present study aimed to develop a real-time allele-specific oligonucleotide PCR (ASO-RQ-PCR) to detect the MYD88 L265P mutation. We first evaluated the reproducibility and sensitivity of the technique with a diluting experiment of a previously known positive sample. Then, we evaluated the applicability of the methodology by analyzing 30 selected patients (10 asymptomatic WM, 10 symptomatic WM, and 10 IgM MGUS) as well as 10 healthy donors. The quantitative ASO-PCR assay could detect the MYD88 L265P mutation at a dilution of 0.25%, showing an inverse correlation between the tumor cell percentage and the cycle threshold (CT) value, thus allowing for tumor burden quantitation. In addition, mutated cases were distinguished from the unmutated by >10 cycles of difference between CTs. To sum up, ASO-RQ-PCR is an inexpensive, robust, and optimized method for the detection of MYD88 L265P mutation, which could be considered as a useful molecular tool during the diagnostic work-up of B-cell lymphoproliferative disorders.