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NSJ Bioreagents cd1a antibody
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Abcam mouse monoclonal antibody
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NSJ Bioreagents cd68 antibody
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NSJ Bioreagents map kinase antibody, activated
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DIAGENODE DIAGNOSTICS h3k27me3 antibody
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Cell Signaling Technology Inc ros1 ihc
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Abnova monoclonal mouse anti-foxm1 antibody clone 3a9
PANC1 cells were used as a positive control. (a) The results of the quantitative RT-PCR analyses of <t>FOXM1</t> mRNA expression. The relative transcript levels of FOXM1 normalized to the level in PANC1 are shown. (b) The expression of FOXM1 proteins in the malignant melanoma cell lines and NHEM. (c) The results of the quantitative RT-PCR analyses of the miR-370 mRNA expression. (d) The results of the semiquantitative RT-PCR using primers that can detect three splicing variants: FOXM1a (472bp), FOXM1b (323bp) and FOXM1c (368bp).
Monoclonal Mouse Anti Foxm1 Antibody Clone 3a9, supplied by Abnova, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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OptiView Technologies optiview amplifier multimer
PANC1 cells were used as a positive control. (a) The results of the quantitative RT-PCR analyses of <t>FOXM1</t> mRNA expression. The relative transcript levels of FOXM1 normalized to the level in PANC1 are shown. (b) The expression of FOXM1 proteins in the malignant melanoma cell lines and NHEM. (c) The results of the quantitative RT-PCR analyses of the miR-370 mRNA expression. (d) The results of the semiquantitative RT-PCR using primers that can detect three splicing variants: FOXM1a (472bp), FOXM1b (323bp) and FOXM1c (368bp).
Optiview Amplifier Multimer, supplied by OptiView Technologies, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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OptiView Technologies optiview hrp multimer
PANC1 cells were used as a positive control. (a) The results of the quantitative RT-PCR analyses of <t>FOXM1</t> mRNA expression. The relative transcript levels of FOXM1 normalized to the level in PANC1 are shown. (b) The expression of FOXM1 proteins in the malignant melanoma cell lines and NHEM. (c) The results of the quantitative RT-PCR analyses of the miR-370 mRNA expression. (d) The results of the semiquantitative RT-PCR using primers that can detect three splicing variants: FOXM1a (472bp), FOXM1b (323bp) and FOXM1c (368bp).
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DIAGENODE DIAGNOSTICS antibody clone a0821d
PANC1 cells were used as a positive control. (a) The results of the quantitative RT-PCR analyses of <t>FOXM1</t> mRNA expression. The relative transcript levels of FOXM1 normalized to the level in PANC1 are shown. (b) The expression of FOXM1 proteins in the malignant melanoma cell lines and NHEM. (c) The results of the quantitative RT-PCR analyses of the miR-370 mRNA expression. (d) The results of the semiquantitative RT-PCR using primers that can detect three splicing variants: FOXM1a (472bp), FOXM1b (323bp) and FOXM1c (368bp).
Antibody Clone A0821d, supplied by DIAGENODE DIAGNOSTICS, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Cell Signaling Technology Inc egfrl858r rabbit
( A ) Computed tomography indicates the clinical course and timeline of disease in the patient with rapid progression on EGFR TKI therapy and shows the EGFR-mutant lung adenocarcinoma (red arrows) analyzed both prior to erlotinib treatment and upon resistance at 4 months. ( B ) Key somatic mutations identified by exon-capture and deep sequencing of the pre- and post-treatment tumor in ( A ) demonstrating concurrent alterations in EGFR and BRAF and the frequency of each mutation in pre- and post- treatment tumor samples. P-values indicated as determined by a two-tailed Fischer’s exact test. ( C ) DNA copy number alterations inferred from exon-capture and sequencing data indicate the focal amplification of the <t>EGFRL858R-mutant</t> allele was lost upon acquired resistance while the patient’s resistant tumor gained a focal amplification of MET, with no change in BRAF (relative positions indicated, chromosome 7).
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Image Search Results


PANC1 cells were used as a positive control. (a) The results of the quantitative RT-PCR analyses of FOXM1 mRNA expression. The relative transcript levels of FOXM1 normalized to the level in PANC1 are shown. (b) The expression of FOXM1 proteins in the malignant melanoma cell lines and NHEM. (c) The results of the quantitative RT-PCR analyses of the miR-370 mRNA expression. (d) The results of the semiquantitative RT-PCR using primers that can detect three splicing variants: FOXM1a (472bp), FOXM1b (323bp) and FOXM1c (368bp).

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: PANC1 cells were used as a positive control. (a) The results of the quantitative RT-PCR analyses of FOXM1 mRNA expression. The relative transcript levels of FOXM1 normalized to the level in PANC1 are shown. (b) The expression of FOXM1 proteins in the malignant melanoma cell lines and NHEM. (c) The results of the quantitative RT-PCR analyses of the miR-370 mRNA expression. (d) The results of the semiquantitative RT-PCR using primers that can detect three splicing variants: FOXM1a (472bp), FOXM1b (323bp) and FOXM1c (368bp).

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Positive Control, Quantitative RT-PCR, Expressing, Reverse Transcription Polymerase Chain Reaction

The FOXM1 expression (normalized to GAPDH) in the patients with primary melanoma (n = 25), metastatic melanoma (n = 9) and nevi (n = 10) is shown. The bars indicate the median values.

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: The FOXM1 expression (normalized to GAPDH) in the patients with primary melanoma (n = 25), metastatic melanoma (n = 9) and nevi (n = 10) is shown. The bars indicate the median values.

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Expressing

Representative images of the immunohistochemical staining for FOXM1 in primary malignant melanoma (a, b, c, d, e) and nevus tissues samples (f, g, h). Hematoxylin and eosin staining (a, f: × 40) and FOXM1 immunohistochemistry (b, g: × 40, c, h: × 400). Negative controls using an isotype monoclonal antibody were presented in d and e (d: × 40, e: × 400). Melanin granules are indicated by blue staining, although they did not exhibit FOXM1 expression. Bars: 500 μm (a, b, d, f, g), 50 μm (c, e, h).

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: Representative images of the immunohistochemical staining for FOXM1 in primary malignant melanoma (a, b, c, d, e) and nevus tissues samples (f, g, h). Hematoxylin and eosin staining (a, f: × 40) and FOXM1 immunohistochemistry (b, g: × 40, c, h: × 400). Negative controls using an isotype monoclonal antibody were presented in d and e (d: × 40, e: × 400). Melanin granules are indicated by blue staining, although they did not exhibit FOXM1 expression. Bars: 500 μm (a, b, d, f, g), 50 μm (c, e, h).

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Immunohistochemical staining, Staining, Immunohistochemistry, Expressing

The results of the immunohistochemical analysis of  FOXM1.

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: The results of the immunohistochemical analysis of FOXM1.

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Immunohistochemical staining

The results of the immunohistochemical analysis of  FOXM1,  BRAFV600E and p-AKT.

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: The results of the immunohistochemical analysis of FOXM1, BRAFV600E and p-AKT.

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Immunohistochemical staining

The correlation between  FOXM1  expression and the tumor thickness.

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: The correlation between FOXM1 expression and the tumor thickness.

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Expressing

A comparison of the overall survival between the patients positive for FOXM1 and those negative for expression, as determined using immunohistochemical staining. The p -values were determined using the log-rank test.

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: A comparison of the overall survival between the patients positive for FOXM1 and those negative for expression, as determined using immunohistochemical staining. The p -values were determined using the log-rank test.

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Comparison, Expressing, Immunohistochemical staining, Staining

The human melanoma cell lines, MeWo and SK-MEL28, were transfected with control and FOXM1 siRNA. Twenty-four hours after treatment, the quantitative RT-PCR analyses were carried out (a,). Seventy-two hours after treatment, a Western blotting analysis and the BrdU cell proliferation assay were performed (b, c). The p -values were determined using the Mann–Whitney U-test. * p < 0.05.

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: The human melanoma cell lines, MeWo and SK-MEL28, were transfected with control and FOXM1 siRNA. Twenty-four hours after treatment, the quantitative RT-PCR analyses were carried out (a,). Seventy-two hours after treatment, a Western blotting analysis and the BrdU cell proliferation assay were performed (b, c). The p -values were determined using the Mann–Whitney U-test. * p < 0.05.

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Transfection, Control, Quantitative RT-PCR, Western Blot, BrdU Cell Proliferation Assay, MANN-WHITNEY

The expression of FOXM1 was assessed using a Western blotting analysis. The human melanoma cell lines were treated with 10 μM of MEK1 siRNA for 72 hours.

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: The expression of FOXM1 was assessed using a Western blotting analysis. The human melanoma cell lines were treated with 10 μM of MEK1 siRNA for 72 hours.

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Expressing, Western Blot

(a) The expression of activated AKT was assessed by a Western blotting analysis using phospho-specific anti-AKT antibodies. (b) The results of the Western blotting analysis of the cell lysates from the human melanoma cell lines treated with LY294002 (30 μM) and an AKT inhibitor (20 μM) for 24 hours. The levels of FOXM1, p-AKT (ser 473) and AKT were determined. (c) Melanoma cell lines were transfected with control or FOXM1 siRNA, and a Western blotting was carried out with p-AKT (ser 473), AKT and FOXM1 antibodies 72 hours after treatment.

Journal: PLoS ONE

Article Title: Investigation of FOXM1 as a Potential New Target for Melanoma

doi: 10.1371/journal.pone.0144241

Figure Lengend Snippet: (a) The expression of activated AKT was assessed by a Western blotting analysis using phospho-specific anti-AKT antibodies. (b) The results of the Western blotting analysis of the cell lysates from the human melanoma cell lines treated with LY294002 (30 μM) and an AKT inhibitor (20 μM) for 24 hours. The levels of FOXM1, p-AKT (ser 473) and AKT were determined. (c) Melanoma cell lines were transfected with control or FOXM1 siRNA, and a Western blotting was carried out with p-AKT (ser 473), AKT and FOXM1 antibodies 72 hours after treatment.

Article Snippet: Sections of paraffin-embedded melanomas and nevus tissue samples were stained with a monoclonal mouse anti-FOXM1 antibody (clone 3A9; Abnova, Taipei, Taiwan), monoclonal mouse anti-BRAFV600E antibody (clone VE1; Spring Bioscience, Pleasanton, CA) and monoclonal rabbit anti-phospho-AKT (Ser473) antibody (Cell Signaling Technologies, Tokyo, Japan).

Techniques: Expressing, Western Blot, Transfection, Control

( A ) Computed tomography indicates the clinical course and timeline of disease in the patient with rapid progression on EGFR TKI therapy and shows the EGFR-mutant lung adenocarcinoma (red arrows) analyzed both prior to erlotinib treatment and upon resistance at 4 months. ( B ) Key somatic mutations identified by exon-capture and deep sequencing of the pre- and post-treatment tumor in ( A ) demonstrating concurrent alterations in EGFR and BRAF and the frequency of each mutation in pre- and post- treatment tumor samples. P-values indicated as determined by a two-tailed Fischer’s exact test. ( C ) DNA copy number alterations inferred from exon-capture and sequencing data indicate the focal amplification of the EGFRL858R-mutant allele was lost upon acquired resistance while the patient’s resistant tumor gained a focal amplification of MET, with no change in BRAF (relative positions indicated, chromosome 7).

Journal: Scientific Reports

Article Title: Novel computational method for predicting polytherapy switching strategies to overcome tumor heterogeneity and evolution

doi: 10.1038/srep44206

Figure Lengend Snippet: ( A ) Computed tomography indicates the clinical course and timeline of disease in the patient with rapid progression on EGFR TKI therapy and shows the EGFR-mutant lung adenocarcinoma (red arrows) analyzed both prior to erlotinib treatment and upon resistance at 4 months. ( B ) Key somatic mutations identified by exon-capture and deep sequencing of the pre- and post-treatment tumor in ( A ) demonstrating concurrent alterations in EGFR and BRAF and the frequency of each mutation in pre- and post- treatment tumor samples. P-values indicated as determined by a two-tailed Fischer’s exact test. ( C ) DNA copy number alterations inferred from exon-capture and sequencing data indicate the focal amplification of the EGFRL858R-mutant allele was lost upon acquired resistance while the patient’s resistant tumor gained a focal amplification of MET, with no change in BRAF (relative positions indicated, chromosome 7).

Article Snippet: Sections were then incubated with EGFRL858R rabbit (43B2, Cell signaling) and BRAFV600E mouse (VE1, Spring Biosciences) primary antibodies at 1:50 in blocking buffer overnight at 4 °C in a humidified chamber.

Techniques: Computed Tomography, Mutagenesis, Sequencing, Two Tailed Test, Amplification

( A ) A simulation of the mathematical model of lung adenocarcinoma evolution (SI, Equation (S1)) in the presence of 1 μ M erlotinib, given the patient-derived pretreatment initial tumor cell subpopulations (94% EGFRL858R, 6% BRAF V600E, 0.01% MET amplification of EGFRL858R, BRAFV600E and EGFRT790M). Parameters used in the simulation were derived from growth and viability assays of parental 11–18 EGFRL858R-positive lung adenocarcinoma cells or those cells engineered to express mutations listed above and treated with 0 or 50 ng/ml HGF, in the presence of varying concentrations of erlotinib and fit according to Equations S8, S9 and S11. ( B ) Tumor cell populations present at day 0, 6 and 17 of the simulation in ( A ), including the total HGF+ cell population at day 17 (gray). The model qualitatively captures a possible evolutionary trajectory and results in a similar final tumor cell composition as that of the patient, ( B ) day 17 vs. .

Journal: Scientific Reports

Article Title: Novel computational method for predicting polytherapy switching strategies to overcome tumor heterogeneity and evolution

doi: 10.1038/srep44206

Figure Lengend Snippet: ( A ) A simulation of the mathematical model of lung adenocarcinoma evolution (SI, Equation (S1)) in the presence of 1 μ M erlotinib, given the patient-derived pretreatment initial tumor cell subpopulations (94% EGFRL858R, 6% BRAF V600E, 0.01% MET amplification of EGFRL858R, BRAFV600E and EGFRT790M). Parameters used in the simulation were derived from growth and viability assays of parental 11–18 EGFRL858R-positive lung adenocarcinoma cells or those cells engineered to express mutations listed above and treated with 0 or 50 ng/ml HGF, in the presence of varying concentrations of erlotinib and fit according to Equations S8, S9 and S11. ( B ) Tumor cell populations present at day 0, 6 and 17 of the simulation in ( A ), including the total HGF+ cell population at day 17 (gray). The model qualitatively captures a possible evolutionary trajectory and results in a similar final tumor cell composition as that of the patient, ( B ) day 17 vs. .

Article Snippet: Sections were then incubated with EGFRL858R rabbit (43B2, Cell signaling) and BRAFV600E mouse (VE1, Spring Biosciences) primary antibodies at 1:50 in blocking buffer overnight at 4 °C in a humidified chamber.

Techniques: Derivative Assay, Amplification

( A ) Drug efficacy as measured by the effect of 1.5 μ M erlotinib or 0.5 μ M afatinib in combination with either 0.5 μ M MET inhibitor crizotinib, 0.5 μ M MEK inhibitor trametinib or 5 μ M BRAF inhibitor vemurafenib on cell growth (SI, Equation S1) of parental 11–18 EGFRL858R-positive lung adenocarcinoma cells or those cells engineered to express mutations listed above and treated with 0 or 50 ng/ml HGF. ( B ) Concentrations of EGFR TKIs afatinib and erlotinib in combination with either 0.5 μ M crizotinib, 0.5 μ M trametinib or 5 μ M vemurafenib that guarantee progression free tumor reduction for any HGF− or HGF+ initial tumor subpopulations according to the model, measured by the minimum concentration of erlotinib or afatinib that results in exponential stability of the evolutionary dynamics model (SI, Section 3.2). ( C ) Simulations of the lung adenocarcinoma model for combinations of 0.5M afatinib + 0.5 μ M trametinib and 1.5 μ M erlotinib + 0.5 μ M μ crizotinib for the HGF− and HGF+ tumors specified. ( D ) (Left) Simulations of the evolutionary dynamics of different HGF− lung adenocarcinoma initial tumor subpopulations with a constant treatment of 0.7 μ M, 0.5, 0.3 or 0.1 μ M afatinib in combination with 0.5 μ M of trametinib (red) and of different HGF+ lung adenocarcinoma initial tumor subpopulations with a constant treatment of 8.32 μ M, 3.2 μ M, 1.5 μ M or 0.75 μ M erlotinib in combination with 0.5 μ M crizotinib (blue). (Right) Maximum eigenvalue decompositions (SI, Section 3.2) classify which subpopulations can lead to progression at different concentrations of EGFR TKI for the afatinib + trametinib combination and the erlotinib + crizotinib combination.

Journal: Scientific Reports

Article Title: Novel computational method for predicting polytherapy switching strategies to overcome tumor heterogeneity and evolution

doi: 10.1038/srep44206

Figure Lengend Snippet: ( A ) Drug efficacy as measured by the effect of 1.5 μ M erlotinib or 0.5 μ M afatinib in combination with either 0.5 μ M MET inhibitor crizotinib, 0.5 μ M MEK inhibitor trametinib or 5 μ M BRAF inhibitor vemurafenib on cell growth (SI, Equation S1) of parental 11–18 EGFRL858R-positive lung adenocarcinoma cells or those cells engineered to express mutations listed above and treated with 0 or 50 ng/ml HGF. ( B ) Concentrations of EGFR TKIs afatinib and erlotinib in combination with either 0.5 μ M crizotinib, 0.5 μ M trametinib or 5 μ M vemurafenib that guarantee progression free tumor reduction for any HGF− or HGF+ initial tumor subpopulations according to the model, measured by the minimum concentration of erlotinib or afatinib that results in exponential stability of the evolutionary dynamics model (SI, Section 3.2). ( C ) Simulations of the lung adenocarcinoma model for combinations of 0.5M afatinib + 0.5 μ M trametinib and 1.5 μ M erlotinib + 0.5 μ M μ crizotinib for the HGF− and HGF+ tumors specified. ( D ) (Left) Simulations of the evolutionary dynamics of different HGF− lung adenocarcinoma initial tumor subpopulations with a constant treatment of 0.7 μ M, 0.5, 0.3 or 0.1 μ M afatinib in combination with 0.5 μ M of trametinib (red) and of different HGF+ lung adenocarcinoma initial tumor subpopulations with a constant treatment of 8.32 μ M, 3.2 μ M, 1.5 μ M or 0.75 μ M erlotinib in combination with 0.5 μ M crizotinib (blue). (Right) Maximum eigenvalue decompositions (SI, Section 3.2) classify which subpopulations can lead to progression at different concentrations of EGFR TKI for the afatinib + trametinib combination and the erlotinib + crizotinib combination.

Article Snippet: Sections were then incubated with EGFRL858R rabbit (43B2, Cell signaling) and BRAFV600E mouse (VE1, Spring Biosciences) primary antibodies at 1:50 in blocking buffer overnight at 4 °C in a humidified chamber.

Techniques: Concentration Assay

( A ) Switching strategies are more beneficial to tumor cell populations with more initial heterogeneity. (Left) Fold change in final lung adenocarcinoma tumor cell populations at day 30 versus day 0 over the course of the optimal 30, 15, 10, 5, 3, and 1 day treatment strategies solved by algorithm 1 (SI, Section 2.2) and normalized by fold change in final tumor cell population for the constant 30 day treatment strategy for an initial tumor cell population comprised of (90% EGFRL858R, 10% H1975 EGFRL858R, T790M) and another comprised of (89% EGFRL858R, 10% BRAFV600E, 1% EGFRL858R, T790M) subclones. (Right) Sum of fold change for the final lung adenocarcinoma populations (SI, Equation S5) for select initial tumor cell distributions ( , ) and their corresponding optimal 30, 15, 10, 5, 3, and 1 day treatment strategies, categorized by the number of subclones in the initial tumor cell population. Smaller fold change sums indicate that more switching is beneficial to reduce final populations, whereas larger fold changes indicate that more switching does not necessarily help in reducing the final tumor populations. ( B ) EGFR TKI dose perturbations. (Left) Fold change in number of lung adenocarcinoma cells between day 30 and day 0, as a function of percent EGFR TKI dose reduction for the optimal 30, 15, 10, 5 and 1 day strategies solved by algorithm 1 (SI, Section 2.2) for tumor cell populations indicated above. The shaded areas indicate the regions of the perturbation space where the treatment strategy reduces the initial tumor cell population by more than 30% (response, light blue), increases the size of the original tumor population size by more than 20% (progression, red), or maintains the original tumor population size between the two (stability, white). (Right) Bar graphs indicate the maximum reduction in EGFR TKI dose supported by the optimal strategy such that there is still reduction in tumor size at day 30 with respect to day 0 for the V600E and the pretreatment MET tumor. ( C ) The average maximum percent EGFR TKI dose reduction supported before progression for lung adenocarcinoma tumors with different number of initial tumor cell subpopulations and for predicted optimal 30, 15, 10, 5, and 1 day switching strategies.

Journal: Scientific Reports

Article Title: Novel computational method for predicting polytherapy switching strategies to overcome tumor heterogeneity and evolution

doi: 10.1038/srep44206

Figure Lengend Snippet: ( A ) Switching strategies are more beneficial to tumor cell populations with more initial heterogeneity. (Left) Fold change in final lung adenocarcinoma tumor cell populations at day 30 versus day 0 over the course of the optimal 30, 15, 10, 5, 3, and 1 day treatment strategies solved by algorithm 1 (SI, Section 2.2) and normalized by fold change in final tumor cell population for the constant 30 day treatment strategy for an initial tumor cell population comprised of (90% EGFRL858R, 10% H1975 EGFRL858R, T790M) and another comprised of (89% EGFRL858R, 10% BRAFV600E, 1% EGFRL858R, T790M) subclones. (Right) Sum of fold change for the final lung adenocarcinoma populations (SI, Equation S5) for select initial tumor cell distributions ( , ) and their corresponding optimal 30, 15, 10, 5, 3, and 1 day treatment strategies, categorized by the number of subclones in the initial tumor cell population. Smaller fold change sums indicate that more switching is beneficial to reduce final populations, whereas larger fold changes indicate that more switching does not necessarily help in reducing the final tumor populations. ( B ) EGFR TKI dose perturbations. (Left) Fold change in number of lung adenocarcinoma cells between day 30 and day 0, as a function of percent EGFR TKI dose reduction for the optimal 30, 15, 10, 5 and 1 day strategies solved by algorithm 1 (SI, Section 2.2) for tumor cell populations indicated above. The shaded areas indicate the regions of the perturbation space where the treatment strategy reduces the initial tumor cell population by more than 30% (response, light blue), increases the size of the original tumor population size by more than 20% (progression, red), or maintains the original tumor population size between the two (stability, white). (Right) Bar graphs indicate the maximum reduction in EGFR TKI dose supported by the optimal strategy such that there is still reduction in tumor size at day 30 with respect to day 0 for the V600E and the pretreatment MET tumor. ( C ) The average maximum percent EGFR TKI dose reduction supported before progression for lung adenocarcinoma tumors with different number of initial tumor cell subpopulations and for predicted optimal 30, 15, 10, 5, and 1 day switching strategies.

Article Snippet: Sections were then incubated with EGFRL858R rabbit (43B2, Cell signaling) and BRAFV600E mouse (VE1, Spring Biosciences) primary antibodies at 1:50 in blocking buffer overnight at 4 °C in a humidified chamber.

Techniques:

( A ) Simulations of the optimal treatment strategy predicted by algorithm 1 (SI, Section 2.2) consisting of 1.5 μ M erlotinib + 0.5 μ M crizotinib for days (0–5) followed by 0.5 μ M afatinib + 0.5 μ M trametinib for days (5–30); the same strategy but with the switch occurring at day 10 and, constant strategies of 0.5 μ M afatinib + 0.5 μ M trametinib or 1.5 μ M erlotinib + 0.5 μ M crizotinib for 30 days, for an initial tumor cell population of 89% EGFRL858R, 10% EGFRL858RBRAFV600E, 1% EGFRL858R, T790M, HGF treated. ( B ) Evolution experiment shows that the predicted strategy for an initial tumor cell population of 89% EGFRL858R, 10% EGFRL858RBRAFV600E, 1% EGFRL858R, T790M, treated with 50 ng/ml HGF, is optimal. Overlaid numbers indicate the relative cell density of each well at day 30 compared to the erlotinib + crizotinib well (magenta). Computational simulations in ( A ) show that the predicted optimal strategy has the greatest reduction in tumor cells in vitro ( B , red) compared to the same strategy with a 10 day switch (yellow). A simulation of the model predicts that a constant treatment of afatinib + trametinib produces little change in number of tumor cells ( B , blue) and that a constant treatment of erlotinib + crizotinib predicts the exponential outgrowth of the initial EGFRL858R, T790M MET amplified subpopulation, experimentally validated in ( B , magenta).

Journal: Scientific Reports

Article Title: Novel computational method for predicting polytherapy switching strategies to overcome tumor heterogeneity and evolution

doi: 10.1038/srep44206

Figure Lengend Snippet: ( A ) Simulations of the optimal treatment strategy predicted by algorithm 1 (SI, Section 2.2) consisting of 1.5 μ M erlotinib + 0.5 μ M crizotinib for days (0–5) followed by 0.5 μ M afatinib + 0.5 μ M trametinib for days (5–30); the same strategy but with the switch occurring at day 10 and, constant strategies of 0.5 μ M afatinib + 0.5 μ M trametinib or 1.5 μ M erlotinib + 0.5 μ M crizotinib for 30 days, for an initial tumor cell population of 89% EGFRL858R, 10% EGFRL858RBRAFV600E, 1% EGFRL858R, T790M, HGF treated. ( B ) Evolution experiment shows that the predicted strategy for an initial tumor cell population of 89% EGFRL858R, 10% EGFRL858RBRAFV600E, 1% EGFRL858R, T790M, treated with 50 ng/ml HGF, is optimal. Overlaid numbers indicate the relative cell density of each well at day 30 compared to the erlotinib + crizotinib well (magenta). Computational simulations in ( A ) show that the predicted optimal strategy has the greatest reduction in tumor cells in vitro ( B , red) compared to the same strategy with a 10 day switch (yellow). A simulation of the model predicts that a constant treatment of afatinib + trametinib produces little change in number of tumor cells ( B , blue) and that a constant treatment of erlotinib + crizotinib predicts the exponential outgrowth of the initial EGFRL858R, T790M MET amplified subpopulation, experimentally validated in ( B , magenta).

Article Snippet: Sections were then incubated with EGFRL858R rabbit (43B2, Cell signaling) and BRAFV600E mouse (VE1, Spring Biosciences) primary antibodies at 1:50 in blocking buffer overnight at 4 °C in a humidified chamber.

Techniques: In Vitro, Amplification