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A PK/PD Analysis of Circulating Biomarkers and Their Relationship to Tumor Response in Atezolizumab-Treated non-small Cell Lung Cancer Patients
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Pharmetheus AB, Uppsala, Sweden.
Genentech Inc, Dept Clin Pharmacol, San Francisco, CA 94080 USA.
Genentech Inc, Dept Clin Pharmacol, San Francisco, CA 94080 USA.
Genentech Inc, Dept Clin Pharmacol, San Francisco, CA 94080 USA.
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2019 (English)In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 105, no 2, p. 486-495Article in journal (Refereed) Published
Abstract [en]

To assess circulating biomarkers as predictors of antitumor response to atezolizumab (anti-programmed death-ligand 1 (PD-L1), Tecentriq) serum pharmacokinetic (PK) and 95 plasma biomarkers were analyzed in 88 patients with relapsed/refractory non-small cell lung cancer (NSCLC) receiving atezolizumab i.v. q3w (10-20 mg/kg) in the PCD4989g phase I clinical trial. Following exploratory analyses, two plasma biomarkers were chosen for further study and correlation with change in tumor size (the sum of the longest diameter) was assessed in a pharmacokinetic/pharmacodynamic (PK/PD) tumor modeling framework. When longitudinal kinetics of biomarkers and tumor size were modeled, tumor shrinkage was found to significantly correlate with area under the curve (AUC), baseline factors (metastatic sites, liver metastases, and smoking status), and relative change in interleukin (IL)-18 level from baseline at day 21 (RCFBIL-18,d21). Although AUC was a major predictor of tumor shrinkage, the effect was estimated to dissipate with an average half-life of 80 days, whereas RCFBIL-18,d21 seemed relevant to the duration of the response.

Place, publisher, year, edition, pages
WILEY , 2019. Vol. 105, no 2, p. 486-495
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:uu:diva-377669DOI: 10.1002/cpt.1198ISI: 000457465200034PubMedID: 30058723OAI: oai:DiVA.org:uu-377669DiVA, id: diva2:1291500
Note

De två första författarna delar förstaförfattarskapet.

Available from: 2019-02-25 Created: 2019-02-25 Last updated: 2019-08-09Bibliographically approved
In thesis
1. Pharmacometric Evaluation of Biomarkers to Improve Treatment in Oncology
Open this publication in new window or tab >>Pharmacometric Evaluation of Biomarkers to Improve Treatment in Oncology
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cancer is a family of many different diseases with substantial heterogeneity also within the same cancer type. In the era of personalized medicine, it is desirable to identify an early response to treatment (i.e., a biomarker) that can predict the long-term outcome with respect to both safety and efficacy. It is however not uncommon to categorize continuous data, e.g., using tumor size data to classify patients as responders or non-responders, resulting in loss of valuable information. Pharmacometric modeling offers a way of analyzing longitudinal time-courses of different variables (e.g., biomarker and tumor size), and therefore minimizing information loss.

Neutropenia is the most common dose-limiting toxicity for chemotherapeutic drugs and manifests by a low absolute neutrophil count (ANC). This thesis explored the potential of using model-based predictions together with frequent monitoring of the ANC to identify patients at risk of severe neutropenia and potential dose delay. Neutropenia may develop into febrile neutropenia (FN), a potentially life-threatening condition. Interleukin 6, an immune-related biomarker, was identified as an on-treatment predictor of FN in breast cancer patients treated with adjuvant chemotherapy. C-reactive protein, another immune-related biomarker, rather demonstrated confirmatory value to support FN diagnosis.

Cancer immunotherapy is the most recent advance in anticancer treatment, with immune checkpoint inhibitors, e.g., atezolizumab, leading the breakthrough. In a pharmacometric modeling framework, the area under the curve of atezolizumab was related to tumor size changes in non-small cell lung cancer patients treated with atezolizumab. The relative change from baseline of Interleukin 18 at 21 days after start of treatment added predictive value on top of the drug effect. The tumor size time-course predicted overall survival (OS) in the same population.

Circulating tumor cells (CTCs) are tumor cells that have shed from a tumor and circulate in the blood. CTCs may cause distant metastases, which is related to a poor prognosis. A novel modeling framework was developed in which the relationship between tumor size and CTC count was quantified in patients with metastatic colorectal cancer treated with chemotherapy and targeted therapy. It was also demonstrated that the CTC count was a superior predictor of OS in comparison to tumor size changes.

In summary, IL-6 predicted FN, IL-18 predicted tumor size changes and tumor size changes and CTC counts predicted OS. The results in this thesis were obtained by using pharmacometrics to evaluate biomarkers to improve treatment in oncology.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 85
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 275
Keywords
Pharmacometrics, Biomarkers, Oncology, Population PKPD Modeling, NONMEM
National Category
Pharmaceutical Sciences
Research subject
Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-390192 (URN)978-91-513-0709-1 (ISBN)
Public defence
2019-09-27, Room B21, Biomedicinskt centrum (BMC), Husargatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2019-09-05 Created: 2019-08-09 Last updated: 2019-09-17

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