Human Blood Serum Antagonizes Effects of EGFR/HER2-Targeted Drug Lapatinib on Squamous Carcinoma SK-BR-3 Cell Growth and Gene Expression

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Abstract

Lapatinib is a targeted therapeutic inhibiting HER2 and EGFR proteins. It is used for the therapy of HER2-positive breast cancer, although not all the patients respond on it. Using human blood serum samples from 14 female donors (separately taken or combined), we found that human blood serum dramatically abolishes lapatinib inhibition of growth of human breast squamous carcinoma SK-BR-3 cell line. This antagonism between lapatinib and human serum was connected with cancel of drug induced G1/S cell cycle transition arrest. RNA sequencing revealed 308 differentially expressed genes in the presence of lapatinib. Remarkably, when combined with lapatinib, human blood serum showed the capacity of restoring both the rate of cell growth, and the expression of 96.1% of genes that were altered by lapatinib treatment alone. EGF co-administration with lapatinib also restores the cell growth and cancels alteration of 95.8% of genes specific to lapatinib treatment of SK-BR-3 cells. Differential gene expression analysis also showed that in the presence of human serum or EGF, lapatinib was unable to inhibit Toll Like Receptor signaling pathway and alter expression of genes linked with Gene Ontology term of Focal adhesion.

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About the authors

N. A. Shaban

Moscow Institute of Physics and Technology; Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry; The National Medical Research Center for Endocrinology

Email: dkamashev@gmail.com
Russian Federation, Dolgoprudny; Moscow; Moscow

M. M. Raevskiy

Sechenov First Moscow State Medical University

Email: dkamashev@gmail.com
Russian Federation, Moscow

G. S. Zakharova

Sechenov First Moscow State Medical University

Email: dkamashev@gmail.com
Russian Federation, Moscow

V. O. Shipunova

Moscow Institute of Physics and Technology; Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry

Email: dkamashev@gmail.com
Russian Federation, Dolgoprudny; Moscow

S. M. Deyev

Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry; Kazan Federal University

Email: dkamashev@gmail.com
Russian Federation, Moscow; Kazan

M. V. Suntsova

The National Medical Research Center for Endocrinology; Sechenov First Moscow State Medical University

Email: dkamashev@gmail.com
Russian Federation, Moscow; Moscow

M. I. Sorokin

Moscow Institute of Physics and Technology; Sechenov First Moscow State Medical University; European Organization for Research and Treatment of Cancer (EORTC)

Email: dkamashev@gmail.com
Russian Federation, Moscow; Moscow; Brussels, Belgium

A. A. Buzdin

Moscow Institute of Physics and Technology; Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry; The National Medical Research Center for Endocrinology; Sechenov First Moscow State Medical University

Email: dkamashev@gmail.com
Russian Federation, Dolgoprudny; Moscow; Moscow; Moscow

D. E. Kamashev

Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry; The National Medical Research Center for Endocrinology; Sechenov First Moscow State Medical University

Author for correspondence.
Email: dkamashev@gmail.com
Russian Federation, Moscow; Moscow; Moscow

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2. Fig. 1. Growth of SK-BR-3 cells after 7 days of incubation in medium containing FBS (9%) and: a - lapatinib (in nM); b - EGF (in ng/ml). The curves show the average number of cells calculated over three repetitions and normalised to conditions without added drugs

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3. Fig. 2. Growth rate of SK-BR-3 cells in medium containing 5% FBS and 4% human serum obtained from different donors. Growth rate is normalised with respect to the medium containing only FBS (9% FBS; column ‘FBS’)

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4. Fig. 3. Growth rate of SK-BR-3 cells in the presence of lapatinib at a concentration of 75 nM (a) or 150 nM (b) and human serum. The growth medium contained 5% FBS and 4% human serum or 9% FBS (columns ‘FBS’). Columns represent the mean cell growth rate for each donor sample calculated from three replicates, normalised to conditions without lapatinib and human serum (‘no drug’). For all human donor serum samples, the differences between the ‘FBS + lapatinib’ and ‘human serum + lapatinib’ samples were statistically significant (p < 0.05)

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5. Fig. 4. Growth rate of SK-BR-3 cells with increasing concentrations of lapatinib (0-220 nM) in growth medium containing 5% FBS and 4% human serum from four blood samples (sm1, sd12, sd19 and sd27) or 9% FBS (FBS). Cell growth rate versus drug concentration curves for each donor sample were calculated from three replicates normalised to conditions without lapatinib and without human serum

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6. Fig. 5. Growth rate of SK-BR-3 cells upon addition of lapatinib in the presence of EGF at the indicated concentrations. Cell growth rate versus drug concentration curves were calculated using at least three biological replicates of each experiment, normalised to conditions without lapatinib and EGF (curve point ‘without EGF’, at 0 nM lapatinib)

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7. Fig. 6. Distribution of SK-BR-3 cells by phases of the cell cycle after treatment with lapatinib (200 nM) in the presence of EGF (3 ng/ml) or 4% of human blood serum compared with untreated cells ("FBS" – black column). The proportion of cells in the G0/G1 phase and in the S phase is shown. The asterisks indicate statistically significant differences between the samples: * p < 0.05; ** p < 0.01; *** p < 0.001. The analysis of cell distribution by stages of the cell cycle was carried out by FACS method after staining the cells with propidium iodide. Each column represents the mean ± standard deviation in three independent experiments

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8. Fig. 7. Differentially expressed genes (DEG) in a series of comparisons with a cell sample without exposure to drugs for: lapatinib; lapatinib and human blood serum; lapatinib and EGF. DEG is shown in red (log2FC > 1 or log2FC < -1, adjusted p-value < 0.05)

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9. Fig. 8. RNA sequencing of SK-BR-3 cells. Cell growth under the conditions of processing used to collect samples for RNA sequencing (a). Venn diagrams showing the overlap of genes with increased (b) and decreased (c) expression, as well as, together, genes with increased and decreased expression (d) in the presence of: only lapatinib, lapatinib and human serum or lapatinib and EGF. Asterisks indicate the statistical significance of the matches: * p < 0.05; ** p < 0.01; *** p < 0.001

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10. Fig. 9. The terms of the Gene Onthology (GO) database, the most enriched for genes from the set of DEG with increased and decreased expression caused by lapatinib treatment (a) and a set of key lapatinib genes (lapatinib core) (b). Visualized using the R enrichplot package (http://bioconductor.org/packages / release/bioc/html/enrichplot.html). The enrichment of these GO terms is statistically significant (the p-value adjusted according to the Benjamin–Hochberg criterion is less than 0.05)

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11. Fig. 10. 20 of the most strongly activated and inhibited molecular pathways calculated for a set of key lapatinib genes (lapatinib core) in SK-BR-3 cells. The PAL value and the adjusted p-value are shown

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12. Fig. 11. Activation diagram of the NCI Endogenous TLR signaling pathway, presented in the form of an interacting network. The activity of the pathway components compared with the sample without the drug is shown for: cells treated with lapatinib alone (a); groups of key lapatinib genes (Lapatinib core genes) (b); treatment with human blood serum only (c), treatment with human blood serum in combination with lapatinib (d), treatment with EGF only (e), EGF treatment in combination with lapatinib (e). The pathway activation level (PAL) is indicated for each group of DEG compared to conditions without drugs. The green/red arrows indicate activation/inhibition interactions, respectively; the color intensity of the transcription nodes reflects the degree of node activation (the natural logarithm of expression changes along the folds for each node, the geometric mean between expression levels in all samples in the corresponding groups was considered the reference value). Green means activation, red – inhibition, white – non–differential expression, gray - absence of molecular data

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