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A Mathematical Model to Estimate Chemotherapy Concentration at the Tumor-Site and Predict Therapy Response in Colorectal Cancer Patients with Liver Metastases

41 Pages Posted: 15 May 2020 Publication Status: Review Complete

See all articles by Daniel A. Anaya

Daniel A. Anaya

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology

Prashant Dogra

Houston Methodist Research Institute - Mathematics in Medicine Program

Zhihui Wang

Houston Methodist Research Institute - Mathematics in Medicine Program

Mintallah Haider

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology

Jasmina Ehab

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology

Daniel Jeong

H. Lee Moffitt Cancer Center and Research Institute - Department of Radiology

Masoumeh Ghayouri

H. Lee Moffitt Cancer Center and Research Institute - Department of Pathology

Gregory Y. Lauwers

H. Lee Moffitt Cancer Center and Research Institute - Department of Pathology

Kerry Thomas

H. Lee Moffitt Cancer Center and Research Institute - Department of Radiology

Richard Kim

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology

Joseph D. Butner

Houston Methodist Research Institute - Mathematics in Medicine Program

Sara Nizzero

Houston Methodist Research Institute - Department of Nanomedicine; Rice University - Applied Physics Graduate Program

Javier Ruiz Ramírez

Houston Methodist Research Institute - Mathematics in Medicine Program

Marija Plodinec

University of Basel - Biozentrum

Richard L. Sidman

Harvard University - Department of Neurology

Renata Pasqualini

Rutgers University, New Brunswick - Rutgers Cancer Institute of New Jersey

Wadih Arap

Rutgers University, New Brunswick - Rutgers Cancer Institute of New Jersey

Jason B. Fleming

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology

Vittorio Cristini

Houston Methodist Research Institute - Mathematics in Medicine Program

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Abstract

Chemotherapy remains a primary treatment for metastatic cancer, with tumor response to chemotherapy being the benchmark outcome marker. However, therapeutic response in cancer is unpredictable due to significant heterogeneity in drug delivery from systemic circulation to solid tumors, which also remains remarkably understudied. In this proof of concept study, we evaluated chemotherapy concentration at the tumor-site and its association with therapy response by applying a mathematical model of tumor perfusion. Using pre-chemotherapy imaging, clinical and biologic variables, and chemotherapy regimen to inform the model, we estimated tumor-site chemotherapy concentration in patients with colorectal cancer liver metastases, who received chemotherapy prior to surgical hepatic resection with curative-intent. The differential response to therapy in resected specimens, measured with the gold-standard tumor regression grade (TRG; from 1, complete response to 5, no response), was examined relative to the model predicted systemic and tumor-site chemotherapy concentrations. We found t hat average calculated plasma concentration of the cytotoxic drug was essentially equivalent across patients exhibiting different TRGs, while the estimated tumor-site chemotherapeutic concentration (eTSCC) showed a quadratic decline from TRG=1 to TRG=5 ( P < 0.001). The eTSCC was significantly lower than the observed plasma concentration and dropped by a factor of ~5 between patients with complete response (TRG=1) and those with no response (TRG=5), while the plasma concentration remained stable across TRG groups. TRG variations were driven and predicted by differences in tumor perfusion and eTSCC. These findings represent the groundwork that may form the basis of a paradigm shift in the care of potentially curable colorectal cancer with liver metastases and other hypovascular tumors. Notably, this approach can be extended beyond chemotherapy, to therapies where drug concentration at the tumor site is the limiting factor of treatment efficacy, including immunotherapy.

Suggested Citation

Anaya, Daniel A. and Dogra, Prashant and Wang, Zhihui and Haider, Mintallah and Ehab, Jasmina and Jeong, Daniel and Ghayouri, Masoumeh and Lauwers, Gregory Y. and Thomas, Kerry and Kim, Richard and Butner, Joseph D. and Nizzero, Sara and Ramírez, Javier Ruiz and Plodinec, Marija and Sidman, Richard L. and Pasqualini, Renata and Arap, Wadih and Fleming, Jason B. and Cristini, Vittorio, A Mathematical Model to Estimate Chemotherapy Concentration at the Tumor-Site and Predict Therapy Response in Colorectal Cancer Patients with Liver Metastases. Available at SSRN: https://ssrn.com/abstract=3588883 or http://dx.doi.org/10.2139/ssrn.3588883
This version of the paper has not been formally peer reviewed.

Daniel A. Anaya

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology ( email )

Tampa, FL 33612
United States

Prashant Dogra

Houston Methodist Research Institute - Mathematics in Medicine Program ( email )

6670 Bertner Ave.
Houston, TX
United States

Zhihui Wang

Houston Methodist Research Institute - Mathematics in Medicine Program

6670 Bertner Ave.
Houston, TX
United States

Mintallah Haider

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology

Tampa, FL 33612
United States

Jasmina Ehab

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology

Tampa, FL 33612
United States

Daniel Jeong

H. Lee Moffitt Cancer Center and Research Institute - Department of Radiology ( email )

Tampa, FL 33612
United States

Masoumeh Ghayouri

H. Lee Moffitt Cancer Center and Research Institute - Department of Pathology

Tampa, FL 33612
United States

Gregory Y. Lauwers

H. Lee Moffitt Cancer Center and Research Institute - Department of Pathology

Tampa, FL 33612
United States

Kerry Thomas

H. Lee Moffitt Cancer Center and Research Institute - Department of Radiology

Tampa, FL 33612
United States

Richard Kim

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology

Tampa, FL 33612
United States

Joseph D. Butner

Houston Methodist Research Institute - Mathematics in Medicine Program

6670 Bertner Ave.
Houston, TX
United States

Sara Nizzero

Houston Methodist Research Institute - Department of Nanomedicine

6670 Bertner Ave
Houston, TX 77030
United States

Rice University - Applied Physics Graduate Program

6100 South Main Street
Houston, TX 77005-1892
United States

Javier Ruiz Ramírez

Houston Methodist Research Institute - Mathematics in Medicine Program

6670 Bertner Ave.
Houston, TX
United States

Marija Plodinec

University of Basel - Biozentrum ( email )

Klingelbergstrasse 50-70
Basel, CH-4056
Switzerland

Richard L. Sidman

Harvard University - Department of Neurology

Boston, MA
United States

Renata Pasqualini

Rutgers University, New Brunswick - Rutgers Cancer Institute of New Jersey

195 Little Albany Street
New Brunswick, NJ 08903-2681
United States

Wadih Arap

Rutgers University, New Brunswick - Rutgers Cancer Institute of New Jersey

195 Little Albany Street
New Brunswick, NJ 08903-2681
United States

Jason B. Fleming

H. Lee Moffitt Cancer Center and Research Institute - Department of Gastrointestinal Oncology

Tampa, FL 33612
United States

Vittorio Cristini (Contact Author)

Houston Methodist Research Institute - Mathematics in Medicine Program ( email )

6670 Bertner Ave.
Houston, TX
United States

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