scholarly journals Correction: Quantitative systems pharmacology model predictions for efficacy of atezolizumab and nab-paclitaxel in triple-negative breast cancer

2021 ◽  
Vol 9 (10) ◽  
pp. e002100corr1
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Systems Pharmacology ◽  
Quantitative Systems Pharmacology ◽  
Model Predictions ◽  
Systems Pharmacology Model

scholarly journals Quantitative systems pharmacology model predictions for efficacy of atezolizumab and nab-paclitaxel in triple-negative breast cancer

2021 ◽  
Vol 9 (2) ◽  
pp. e002100
Author(s):  
Hanwen Wang ◽  
Huilin Ma ◽  
Richard J Sové ◽  
Leisha A Emens ◽  
Aleksander S Popel
Keyword(s):  
Breast Cancer ◽  
Clinical Trials ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Predictive Biomarkers ◽  
Virtual Patient ◽  
Systems Pharmacology ◽  
Quantitative Systems Pharmacology ◽  
Patient Cohort ◽  
Model Predictions

BackgroundImmune checkpoint blockade therapy has clearly shown clinical activity in patients with triple-negative breast cancer, but less than half of the patients benefit from the treatments. While a number of ongoing clinical trials are investigating different combinations of checkpoint inhibitors and chemotherapeutic agents, predictive biomarkers that identify patients most likely to benefit remains one of the major challenges. Here we present a modular quantitative systems pharmacology (QSP) platform for immuno-oncology that incorporates detailed mechanisms of immune–cancer cell interactions to make efficacy predictions and identify predictive biomarkers for treatments using atezolizumab and nab-paclitaxel.MethodsA QSP model was developed based on published data of triple-negative breast cancer. With the model, we generated a virtual patient cohort to conduct in silico virtual clinical trials and make retrospective analyses of the pivotal IMpassion130 trial that led to the accelerated approval of atezolizumab and nab-paclitaxel for patients with programmed death-ligand 1 (PD-L1) positive triple-negative breast cancer. Available data from clinical trials were used for model calibration and validation.ResultsWith the calibrated virtual patient cohort based on clinical data from the placebo comparator arm of the IMpassion130 trial, we made efficacy predictions and identified potential predictive biomarkers for the experimental arm of the trial using the proposed QSP model. The model predictions are consistent with clinically reported efficacy endpoints and correlated immune biomarkers. We further performed a series of virtual clinical trials to compare different doses and schedules of the two drugs for simulated therapeutic optimization.ConclusionsThis study provides a QSP platform, which can be used to generate virtual patient cohorts and conduct virtual clinical trials. Our findings demonstrate its potential for making efficacy predictions for immunotherapies and chemotherapies, identifying predictive biomarkers, and guiding future clinical trial designs.

A Quantitative Systems Pharmacology Framework for Optimal Doxorubicin Granulocyte Colony-Stimulating Factor Regimens in Triple-Negative Breast Cancer

Pharmacology ◽  
2021 ◽  
pp. 1-9
Author(s):  
Rosalba Vivian Paredes Bonilla ◽  
Fahima Nekka ◽  
Morgan Craig
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Tumour Growth ◽  
Triple Negative ◽  
Effective Control ◽  
Systems Pharmacology ◽  
Granulocyte Colony Stimulating Factor ◽  
Colony Stimulating Factor ◽  
Quantitative Systems Pharmacology ◽  
Stimulating Factor

<b><i>Introduction:</i></b> To mitigate the risk of neutropenia during chemotherapy treatment of triple-negative breast cancer, prophylactic and supportive therapy with granulocyte colony-stimulating factor (G-CSF) is administered concomitant to chemotherapy. The proper timing of combined chemotherapy and G-CSF is crucial for treatment outcomes. <b><i>Methods:</i></b> Leveraging our established mathematical model of neutrophil production by G-CSF, we developed quantitative systems pharmacology (QSP) framework to investigate how modulating chemotherapy dose frequency and intensity can maximize antitumour effects. To establish schedules that best control tumour size while minimizing neutropenia, we combined Gompertzian tumour growth with pharmacokinetic/pharmacodynamic models of doxorubicin and G-CSF, and our QSP model of neutrophil production. <b><i>Results:</i></b> We optimized a range of chemotherapeutic cycle lengths and dose sizes to establish regimens that simultaneously reduced tumour burden while minimizing neutropenia. Our results suggest that cytotoxic chemotherapy with doxorubicin 45 mg/m<sup>2</sup> every 14 days provides effective control of tumour growth while mitigating neutropenic risks. <b><i>Conclusion:</i></b> This work suggests future avenues for optimal regimens of chemotherapy with prophylactic G-CSF support. Importantly, the algorithmic approach that we developed can aid in balancing the anticancer and the neutropenic effects of both drugs, and therefore contributes to rational considerations in clinical decision-making in triple-negative breast cancer.

scholarly journals Systems pharmacology in combination with proteomics reveals underlying mechanisms of Xihuang pill against triple-negative breast cancer

Bioengineered ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 1170-1188
Author(s):  
Xingchao Xu ◽  
Jimei Zhang ◽  
Zhenhua Zhang ◽  
Meng Wang ◽  
Yaping Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Systems Pharmacology ◽  
Underlying Mechanisms

Identification of new therapeutic leads for triple negative breast cancer subtypes

Planta Medica ◽  
2015 ◽  
Vol 81 (11) ◽  
Author(s):  
AJ Robles ◽  
L Du ◽  
S Cai ◽  
RH Cichewicz ◽  
SL Mooberry
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Breast Cancer Subtypes ◽  
Cancer Subtypes ◽  
Therapeutic Leads

Immediate and long-term results of the first line chemotherapy in patients with metastatic triple negative breast cancer. Final analysis of randomized study

2020 ◽  
pp. 75-80
Author(s):  
S.A. Lyalkin ◽  
◽  
L.A. Syvak ◽  
N.O. Verevkina ◽  
◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Randomized Study ◽  
Progression Free Survival ◽  
First Line ◽  
Free Survival ◽  
Group 2 ◽  
Line Chemotherapy ◽  
Group 1

The objective: was to evaluate the efficacy of the first line chemotherapy in patients with metastatic triple negative breast cancer (TNBC). Materials and methods. Open randomized study was performed including 122 patients with metastatic TNBC. The efficacy and safety of the first line chemotherapy of regimens АТ (n=59) – group 1, patients received doxorubicine 60 мг/м2 and paclitaxel 175 мг/м2 and ТР (n=63) – group 2, patients received paclitaxel 175 мг/м2 and carboplatin AUC 5 were evaluated. Results. The median duration of response was 9.5 months (4.5–13.25 months) in patients received AT regimen and 8.5 months (4.7–12.25 months), in TP regimen; no statistically significant differences were observed, р=0.836. The median progression free survival was 7 months (95% CI 5–26 months) in group 1 and 7.5 months (95% CI 6–35 months) in group 2, p=0.85. Both chemotherapy regimens (AT and TP) had mild or moderate toxicity profiles (grade 1 or 2 in most patients). No significant difference in gastrointestinal toxicity was observed. The incidence of grade 3–4 neutropenia was higher in patients of group 2 (TP regimen): 42.8% versus 27% (р<0.05). Conclusions. Both regimens of chemotherapy (AT and TP) are appropriate to use in the first line setting in patients with metastatic TNBC. Key words: metastatic triple negative breast cancer, chemotherapy, progression free survival, chemotherapy toxicity.

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