Early prediction of clinical response to checkpoint inhibitor therapy in human solid tumors through mathematical modeling
- The Houston Methodist Research Institute, United States
- The University of Texas MD Anderson Cancer Center, United States
- University of Texas Health Science Center, United States
- Brigham and Women's Hospital, United States
- Baylor College of Medicine, United States
- Rutgers University, United States
- Harvard Medical School, United States
- Rutgers Cancer Institute of New Jersey, United States
- University of Texas MD Anderson Cancer Center, United States
Abstract
Background: Checkpoint inhibitor therapy of cancer has led to markedly improved survival of a subset of patients in multiple solid malignant tumor types, yet the factors driving these clinical responses or lack thereof are not known. We have developed a mechanistic mathematical model for better understanding these factors and their relations in order to predict treatment outcome and optimize personal treatment strategies.
Methods: Here, we present a translational mathematical model dependent on three key parameters for describing efficacy of checkpoint inhibitors in human cancer: tumor growth rate (α), tumor immune infiltration (Λ), and immunotherapy-mediated amplification of anti-tumor response (µ). The model was calibrated by fitting it to a compiled clinical tumor response dataset (n = 189 patients) obtained from published anti-PD-1 and anti-PD-L1 clinical trials, and then validated on an additional validation cohort (n = 64 patients) obtained from our in-house clinical trials.
Results: The derived parameters Λ and µ were both significantly different between responding versus non-responding patients. Of note, our model appropriately classified response in 81.4% of patients by using only tumor volume measurements and within two months of treatment initiation in a retrospective analysis. The model reliably predicted clinical response to the PD-1/PD-L1 class of checkpoint inhibitors across multiple solid malignant tumor types. Comparison of model parameters to immunohistochemical measurement of PD-L1 and CD8+ T cells confirmed robust relationships between model parameters and their underlying biology.
Conclusion: These results have demonstrated reliable methods to inform model parameters directly from biopsy samples, which are conveniently obtainable as early as the start of treatment. Together, these suggest that the model parameters may serve as early and robust biomarkers of the efficacy of checkpoint inhibitor therapy on an individualized per-patient basis.
Funding: We gratefully acknowledge support from the Andrew Sabin Family Fellowship, Center for Radiation Oncology Research, Sheikh Ahmed Center for Pancreatic Cancer Research, GE Healthcare, Philips Healthcare, and institutional funds from the University of Texas M.D. Anderson Cancer Center. We have also received Cancer Center Support Grants from the National Cancer Institute (P30CA016672 to the University of Texas M.D. Anderson Cancer Center and P30CA072720 the Rutgers Cancer Institute of New Jersey). This research has also been supported in part by grants from the National Science Foundation Grant DMS-1930583 (Z.W., V.C.), the National Institutes of Health (NIH) 1R01CA253865 (Z.W., V.C.), 1U01CA196403 (Z.W., V.C.), 1U01CA213759 (Z.W., V.C.), 1R01CA226537 (Z.W., R.P., W.A., V.C.), 1R01CA222007 (Z.W., V.C.), U54CA210181 (Z.W., V.C.), and the University of Texas System STARS Award (V.C.). B.C. acknowledges support through the SER Cymru II Programme, funded by the European Commission through the Horizon 2020 Marie Skłodowska-Curie Actions (MSCA) COFUND scheme and the Welsh European Funding Office (WEFO) under the European Regional Development Fund (ERDF). E.K. has also received support from the Project Purple, NIH (U54CA210181, U01CA200468, and U01CA196403), and the Pancreatic Cancer Action Network (16-65-SING). M.F. was supported through NIH/NCI center grant U54CA210181, R01CA222959, DoD Breast Cancer Research Breakthrough Level IV Award W81XWH-17-1-0389, and the Ernest Cockrell Jr. Presidential Distinguished Chair at Houston Methodist Research Institute. R.P. and W.A. received serial research awards from AngelWorks, the Gillson-Longenbaugh Foundation, and the Marcus Foundation. This work was also supported in part by grants from the National Cancer Institute to S.H.C. (R01CA109322, R01CA127483, R01CA208703, and U54CA210181 CITO pilot grant) and to P.Y.P. (R01CA140243, R01CA188610, and U54CA210181 CITO pilot grant). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Data availability
No new clinical patient data was produced in this study. Data used that was obtained from literature is available in the original publications; we have been careful to cite each of these in the manuscript. Interested researchers should reach out directly to the primary authors of these studies. Data for the in-house clinical trial cohort are from the study reported in PMC7555111; interested researchers should contact the authors of this publication with any data requests.
Article and author information
Author details
Funding
National Science Foundation (DMS-1930583)
- Zhihui Wang
- Vittorio Cristini
European Commission (SER Cymru II Programme)
- Bruna Corradetti
National Institutes of Health (U01CA200468)
- Eugene J Koay
National Institutes of Health (R01CA222959)
- Mauro Ferrari
DOD Breast Cancer Research (Breakthrough Level IV Award W81XWH-17-1-0389)
- Mauro Ferrari
AngelWorks
- Renata Pasqualini
- Wadih Arap
Gillson-Longenbaugh Foundation
- Renata Pasqualini
- Wadih Arap
Marcus Foundation
- Renata Pasqualini
- Wadih Arap
National Institutes of Health (R01CA109322)
- Shu-Hsia Chen
National Institutes of Health (R01CA127483)
- Shu-Hsia Chen
National Institutes of Health (R01CA208703)
- Shu-Hsia Chen
National Institutes of Health (1R01CA253865)
- Zhihui Wang
- Vittorio Cristini
National Institutes of Health (R01CA140243)
- Ping-Ying Pan
National Institutes of Health (R01CA188610)
- Ping-Ying Pan
National Institutes of Health (1U01CA196403)
- Zhihui Wang
- Eugene J Koay
- Vittorio Cristini
National Institutes of Health (1U01CA213759)
- Zhihui Wang
- Vittorio Cristini
National Institutes of Health (1R01CA226537)
- Zhihui Wang
- Renata Pasqualini
- Wadih Arap
- Vittorio Cristini
National Institutes of Health (1R01CA222007)
- Zhihui Wang
- Vittorio Cristini
National Institutes of Health (U54CA210181)
- Zhihui Wang
- Mauro Ferrari
- Shu-Hsia Chen
- Ping-Ying Pan
- Eugene J Koay
- Vittorio Cristini
National Institutes of Health (P30CA016672)
- David S Hong
- James W Welsh
- Eugene J Koay
National Institutes of Health (P30CA072720)
- Steven K Libutti
- Shridar Ganesan
- Renata Pasqualini
- Wadih Arap
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Caigang Liu, Shengjing Hospital of China Medical University, China
Ethics
Human subjects: In-house patient cohort were obtained as de-identified data from a study conducted in accordance with the U.S. Common Rule and with Institutional Review Board Approval at MD Anderson (2014-1020), including waiver of informed consent. This work has been published in J Immunother Cancer. 2020; 8(2): e001001. PMC7555111. doi: 10.1136/jitc-2020-001001
Version history
- Received: May 6, 2021
- Accepted: October 25, 2021
- Accepted Manuscript published: November 9, 2021 (version 1)
- Version of Record published: November 29, 2021 (version 2)
Copyright
© 2021, Butner et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Early prediction of clinical response to checkpoint inhibitor therapy in human solid tumors through mathematical modeling
eLife 10:e70130.
https://doi.org/10.7554/eLife.70130
Further reading
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- Immunology and Inflammation
- Medicine
Background:
Prinflammatory extracellular chromatin from neutrophil extracellular traps (NETs) and other cellular sources is found in COVID-19 patients and may promote pathology. We determined whether pulmonary administration of the endonuclease dornase alfa reduced systemic inflammation by clearing extracellular chromatin.
Methods:
Eligible patients were randomized (3:1) to the best available care including dexamethasone (R-BAC) or to BAC with twice-daily nebulized dornase alfa (R-BAC + DA) for seven days or until discharge. A 2:1 ratio of matched contemporary controls (CC-BAC) provided additional comparators. The primary endpoint was the improvement in C-reactive protein (CRP) over time, analyzed using a repeated-measures mixed model, adjusted for baseline factors.
Results:
We recruited 39 evaluable participants: 30 randomized to dornase alfa (R-BAC +DA), 9 randomized to BAC (R-BAC), and included 60 CC-BAC participants. Dornase alfa was well tolerated and reduced CRP by 33% compared to the combined BAC groups (T-BAC). Least squares (LS) mean post-dexamethasone CRP fell from 101.9 mg/L to 23.23 mg/L in R-BAC +DA participants versus a 99.5 mg/L to 34.82 mg/L reduction in the T-BAC group at 7 days; p=0.01. The anti-inflammatory effect of dornase alfa was further confirmed with subgroup and sensitivity analyses on randomised participants only, mitigating potential biases associated with the use of CC-BAC participants. Dornase alfa increased live discharge rates by 63% (HR 1.63, 95% CI 1.01–2.61, p=0.03), increased lymphocyte counts (LS mean: 1.08 vs 0.87, p=0.02) and reduced circulating cf-DNA and the coagulopathy marker D-dimer (LS mean: 570.78 vs 1656.96 μg/mL, p=0.004).
Conclusions:
Dornase alfa reduces pathogenic inflammation in COVID-19 pneumonia, demonstrating the benefit of cost-effective therapies that target extracellular chromatin.
Funding:
LifeArc, Breathing Matters, The Francis Crick Institute (CRUK, Medical Research Council, Wellcome Trust).
Clinical trial number:
-
- Medicine
Background:
Adverse effects of proton pump inhibitors (PPIs) have raised wide concerns. The association of PPIs with influenza is unexplored, while that with pneumonia or COVID-19 remains controversial. Our study aims to evaluate whether PPI use increases the risks of these respiratory infections.
Methods:
The current study included 160,923 eligible participants at baseline who completed questionnaires on medication use, which included PPI or histamine-2 receptor antagonist (H2RA), from the UK Biobank. Cox proportional hazards regression and propensity score-matching analyses were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs).
Results:
Comparisons with H2RA users were tested. PPI use was associated with increased risks of developing influenza (HR 1.32, 95% CI 1.12–1.56) and pneumonia (hazard ratio [HR] 1.42, 95% confidence interval [CI] 1.26–1.59). In contrast, the risk of COVID-19 infection was not significant with regular PPI use (HR 1.08, 95% CI 0.99–1.17), while the risks of severe COVID-19 (HR 1.19. 95% CI 1.11–1.27) and mortality (HR 1.37. 95% CI 1.29–1.46) were increased. However, when compared with H2RA users, PPI users were associated with a higher risk of influenza (HR 1.74, 95% CI 1.19–2.54), but the risks with pneumonia or COVID-19-related outcomes were not evident.
Conclusions:
PPI users are associated with increased risks of influenza, pneumonia, as well as COVID-19 severity and mortality compared to non-users, while the effects on pneumonia or COVID-19-related outcomes under PPI use were attenuated when compared to the use of H2RAs. Appropriate use of PPIs based on comprehensive evaluation is required.
Funding:
This work is supported by the National Natural Science Foundation of China (82171698, 82170561, 81300279, 81741067, 82100238), the Program for High-level Foreign Expert Introduction of China (G2022030047L), the Natural Science Foundation for Distinguished Young Scholars of Guangdong Province (2021B1515020003), the Guangdong Basic and Applied Basic Research Foundation (2022A1515012081), the Foreign Distinguished Teacher Program of Guangdong Science and Technology Department (KD0120220129), the Climbing Program of Introduced Talents and High-level Hospital Construction Project of Guangdong Provincial People’s Hospital (DFJH201923, DFJH201803, KJ012019099, KJ012021143, KY012021183), and in part by VA Clinical Merit and ASGE clinical research funds (FWL).
