Dynamics of Tumor and Immune Responses during Immune Checkpoint Blockade in Non–Small Cell Lung Cancer

Anagnostou, Valsamo; Forde, Patrick M.; White, James R.; Niknafs, Noushin; Hruban, Carolyn; Naidoo, Jarushka; Marrone, Kristen A.; Sivakumar, I.K. Ashok; Bruhm, Daniel C.; Rosner, Samuel; Phallen, Jillian; Leal, Alessandro; Adleff, Vilmos; Smith, Kellie N.; Cottrell, Tricia R.; Rhymee, Lamia; Palsgrove, Doreen N.; Hann, Christine L.; Levy, Benjamin; Feliciano, Josephine; Georgiades, Christos; Verde, Franco; Illei, Peter B.; Li, Qing Kay; Gabrielson, Edward; Brock, Malcolm V.; Isbell, James M.; Sauter, Jennifer L.; Taube, Janis M.; Scharpf, Robert B.; Karchin, Rachel; Pardoll, Drew M.; Chaft, Jamie E.; Hellmann, Matthew D.; Brahmer, Julie R.; Velculescu, Victor E.

doi:10.1158/0008-5472.can-18-1127

Cited by 245 publications

(256 citation statements)

References 39 publications

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“…Another strategy for TCR clonotype dynamics during CBI is to focus on peripheral TCR clones that show a differential abundance between baseline and the defined time point (e.g., after each dose of drug, or objective clinical responses) [81]. The analysis can be refined by considering the peripheral TCR clones also found in the tumor [86]. The average productive frequency of these differentially abundant clones can be used as a metric of TCR dynamics during therapy [86].…”

Section: Analysis Of Immune Repertoirementioning

confidence: 99%

“…The analysis can be refined by considering the peripheral TCR clones also found in the tumor [86]. The average productive frequency of these differentially abundant clones can be used as a metric of TCR dynamics during therapy [86]. The main TCR repertoire metrics used as biomarkers in major CBI studies are summarized in Table 3.…”

Section: Analysis Of Immune Repertoirementioning

confidence: 99%

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Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Aversa

Malanga

Fiume

et al. 2020

IJMS

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The T cells are key players of the response to checkpoint blockade immunotherapy (CBI) and monitoring the strength and specificity of antitumor T-cell reactivity remains a crucial but elusive component of precision immunotherapy. The entire assembly of T-cell receptor (TCR) sequences accounts for antigen specificity and strength of the T-cell immune response. The TCR repertoire hence represents a “footprint” of the conditions faced by T cells that dynamically evolves according to the challenges that arise for the immune system, such as tumor neo-antigenic load. Hence, TCR repertoire analysis is becoming increasingly important to comprehensively understand the nature of a successful antitumor T-cell response, and to improve the success and safety of current CBI.

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Section: Analysis Of Immune Repertoirementioning

confidence: 99%

Section: Analysis Of Immune Repertoirementioning

confidence: 99%

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Aversa

Malanga

Fiume

et al. 2020

IJMS

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“…7 Likewise, early changes in ctDNA in other cancers have correlated with long-term outcomes to anti-PD1 therapy and if reproduced in NPC, it may help guide future combination IO strategies. 65,66 In addition to these well-known markers, more comprehensive exploratory analysis will be conducted on materials collected in these trials to generate hypotheses on mechanisms of response, innate resistance, and adaptive resistance to ICI in NPC. We have previously provided a comprehensive list of IO biomarkers in head and neck cancers, including those from the tumor, peripheral blood, stool, saliva or imaging studies in the written summary of our CTPM on Immunotherapy of Head and Neck Cancer.…”

Section: Correlative Biomarkersmentioning

confidence: 99%

Current Treatment Landscape of Nasopharyngeal Carcinoma and Potential Trials Evaluating the Value of Immunotherapy

Colevas

O’Sullivan

et al. 2019

JNCI: Journal of the National Cancer Institute

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Nasopharyngeal carcinoma (NPC) is a type of head and neck cancer with a distinctive regional and racial prevalence. It is associated with Epstein-Barr virus infection and has a high propensity for regional and distant metastases, while it is very sensitive to radiation and chemotherapy. A common feature of Epstein-Barr virus-positive NPC is the dense infiltration of lymphocytes in the tumor stroma and positive programmed death-ligand 1 expression in tumor cells, making it an attractive target for immunotherapy, especially immune checkpoint inhibitors. As new immunotherapeutic agents are being rapidly adopted in many cancers, including head and neck cancer, the National Cancer Institute sponsored a clinical trial planning meeting to identify opportunities for developing phase II and III trials testing immunotherapy in different stages of NPC. The meeting started with the summary of the biology of the disease, current standards of care, and evidence of immunotherapy in this cancer. Three subcommittees were tasked to develop clinical trials: loco regionally advanced, nonmetastatic NPC; widely metastatic NPC; and either local recurrence after initial treatment or presenting with oligometastatic disease. This article summarizes the proceedings of this clinical trial planning meeting and provides a road map for future trials incorporating immune checkpoint inhibitors for therapeutic management of NPC. This road map, though specific for NPC, may also be applicable to other virally driven cancers that have similar ability to evade the host’s immune system.

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“…In addition, due to the complex dynamic responses elicited by the immune system against tumor cells [16] [17], and also inherent noise and fluctuations in signaling pathways and regulatory networks that control different functions of cells, and uncertainty in the kinetic/dynamic rate of tumor-immune system interactions [18], there is a demanding need for new class of computational models to predict dynamics of TIS agents in uncertain environment.…”

mentioning

confidence: 99%

In Silico Assessment of 5-FU Therapy via A Mathematical Model with Fuzzy Uncertain Parameters

Shafiekhani¹,

Jafari‬²,

Jafarzadeh³

et al. 2020

Preprint

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Abstract Background: Ordinary differential equation (ODE) models widely have been used in mathematical oncology to capture dynamics of tumor and immune cells and evaluate the efficacy of treatments. However, for dynamic models of tumor-immune system (TIS), some parameters are uncertain due to inaccurate, missing or incomplete data, which has hindered the application of ODEs that require accurate parameters. Methods: We extended an available ODE model of TIS interactions via fuzzy logic to illustrate the fuzzification procedure of an ODE model. Fuzzy ODE (FODE) models, in comparison with the stochastic differential equation (SDE) models, assigns a fuzzy number instead of a random number (from a specific probability density function) to the parameters, to capture parametric uncertainty. We used FODE model to predict tumor and immune cells dynamics and assess the efficacy of 5-FU. The present model is configurable for 5-FU chemotherapy injection timing and propose testable hypothesis in vitro/ in vivo experiments. Result: FODE model was used to explore the uncertainty of cells dynamics resulting from parametric uncertainty in presence and absence of 5-FU therapy. In silico experiments revealed that the frequent 5-FU injection created a beneficial tumor microenvironment that exerted detrimental effects on tumor cells by enhancing the infiltration of CD8+ T cells, and NK cells, and decreasing that of myeloid-derived suppressor (MDSC) cells. We investigate the effect of perturbation on model parameters on dynamics of cells through global sensitivity analysis (GSA) and compute correlation between model parameters and cell dynamics. Conclusion: ODE models with fuzzy uncertain kinetic parameters cope with insufficient experimental data in the field of mathematical oncology and can predict cells dynamics uncertainty band. In silico assessment of treatments considering parameter uncertainty and investigating the effect of the drugs on movement of cells dynamics uncertainty band may be more appropriate than in crisp setting.

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Dynamics of Tumor and Immune Responses during Immune Checkpoint Blockade in Non–Small Cell Lung Cancer

Cited by 245 publications

References 39 publications

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Current Treatment Landscape of Nasopharyngeal Carcinoma and Potential Trials Evaluating the Value of Immunotherapy

In Silico Assessment of 5-FU Therapy via A Mathematical Model with Fuzzy Uncertain Parameters

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