Differential effects of two therapeutic cancer vaccines on short- and long-term survival populations among patients with advanced lung cancer

Sánchez, Lizet; Muchene, Leacky; Lorenzo-Luaces, Patricia; Viada, Carmen; Rodríguez, Pedro C.; Alfonso, Sailyn; Crombet, Tania; Neninger, Elia; Shkedy, Ziv; Lage, Agustín

doi:10.1053/j.seminoncol.2018.04.005

Cited by 10 publications

(9 citation statements)

References 18 publications

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“…These experiments suggest that this vaccine platform might prove useful for targeting peptide epitopes in therapeutic settings, such as allergy, cancer, hypertension, and animal health. 33–35…”

Section: Discussionmentioning

confidence: 99%

Epitope targeting with self-assembled peptide vaccines

et al. 2019

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Nanoparticle-based delivery systems are being used to simplify and accelerate new vaccine development. Previously, we described the solid-phase synthesis of a 61-amino acid conjugate vaccine carrier comprising a α-helical domain followed by two universal T cell epitopes. Circular dichroism, analytical centrifugation, and dynamic light scattering indicate that this carrier forms coiled-coil nanoparticles. Here we expand the potential of this carrier by appending B cell epitopes to its amino acid sequence, thereby eliminating the need for traditional conjugation reactions. Peptides containing Tau or amyloid-β epitopes at either terminus assemble into ~20 nm particles and induce antibody responses in outbred mice. Vaccine function was verified in three experiments. The first targeted gonadotropin-releasing hormone, a 10-amino acid neuropeptide that regulates sexual development. Induction of peak antibody titers in male mice stimulated a dramatic loss in fertility and marked testis degeneration. The second experiment generated antibodies to an epitope on the murine IgE heavy chain analogous to human IgE sequence recognized by omalizumab, the first monoclonal antibody approved for the treatment of allergic asthma. Like omalizumab, the anti-IgE antibodies in immunized mice reduced the concentrations of circulating free IgE and prevented IgE-induced anaphylaxis. Finally, a peptide containing the highly conserved Helix A epitope within the influenza hemagglutinin stem domain induced antibodies that successfully protected mice against a lethal H1N1 challenge. These results establish the utility of a new vaccine platform for eliciting prophylactic and therapeutic antibodies to linear and helical B cell epitopes.

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Section: Discussionmentioning

confidence: 99%

Epitope targeting with self-assembled peptide vaccines

et al. 2019

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“…However, there is evidence of heterogeneous responses to the vaccine. Patients with short-term and long-term survival were differentiated between those treated with CIMAvax-EGF [6]. In phase II and phase III trials conducted, the patient developed a "good antibody response" (anti-EGF antibody titers ≥1:4000 sera dilution) seemed to have significantly better survival compared with patients who had lower anti-EGF antibody responses [1,3,4].…”

Section: Introductionmentioning

confidence: 99%

Identifying predictive biomarkers of CIMAvaxEGF success in non–small cell lung cancer patients

et al. 2020

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Background: Immunosenescence biomarkers and peripheral blood parameters are evaluated separately as possible predictive markers of immunotherapy. Here, we illustrate the use of a causal inference model to identify predictive biomarkers of CIMAvaxEGF success in the treatment of Non-Small Cell Lung Cancer Patients. Methods: Data from a controlled clinical trial evaluating the effect of CIMAvax-EGF were analyzed retrospectively, following a causal inference approach. Pre-treatment potential predictive biomarkers included basal serum EGF concentration, peripheral blood parameters and immunosenescence biomarkers. The proportion of CD8 + CD28-T cells, CD4+ and CD8+ T cells, CD4/CD8 ratio and CD19+ B cells. The 33 patients with complete information were included. The predictive causal information (PCI) was calculated for all possible models. The model with a minimum number of predictors, but with high prediction accuracy (PCI > 0.7) was selected. Good, rare and poor responder patients were identified using the predictive probability of treatment success. Results: The mean of PCI increased from 0.486, when only one predictor is considered, to 0.98 using the multivariate approach with all predictors. The model considering the proportion of CD4+ T cell, basal Epidermal Growth Factor (EGF) concentration, neutrophil to lymphocyte ratio, Monocytes, and Neutrophils as predictors were selected (PCI > 0.74). Patients predicted as good responders according to the pre-treatment biomarkers values treated with CIMAvax-EGF had a significant higher observed survival compared with the control group (p = 0.03). No difference was observed for bad responders. Conclusions: Peripheral blood parameters and immunosenescence biomarkers together with basal EGF concentration in serum resulted in good predictors of the CIMAvax-EGF success in advanced NSCLC. Future research should explore molecular and genetic profile as biomarkers for CIMAvax-EGF and it combination with immune-checkpoint inhibitors. The study illustrates the application of a new methodology, based on causal inference, to evaluate multivariate pre-treatment predictors. The multivariate approach allows realistic predictions of the clinical benefit of patients and should be introduced in daily clinical practice.

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“…However, there is evidence of heterogeneous responses to the vaccine. Patients with short-term and long-term survival were differentiated between those treated with CIMAvax-EGF [6]. In phase II and phase III trials conducted, the patient developed a ''good antibody response'' (anti-EGF antibody titers ≥ 1:4,000 sera dilution) seemed to have signi cantly better survival compared with patients who had lower anti-EGF antibody responses [1,3,4].…”

Section: Introductionmentioning

confidence: 99%

Identifying predictive biomarkers of CIMAvaxEGF success in Non–Small Cell Lung Cancer Patients.

Lorenzo-Luaces

Sánchez

Saavedra

et al. 2020

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Background: Immunosenescence biomarkers and peripheral blood parameters are evaluated separately as possible predictive markers of immunotherapy. Here, we illustrate the use of a causal inference model to identify predictive biomarkers of CIMAvaxEGF success in the treatment of Non–Small Cell Lung Cancer Patients. Methods: Data from a controlled clinical trial evaluating the effect of CIMAvax-EGF were analyzed retrospectively, following a causal inference approach. Pre-treatment potential predictive biomarkers included basal serum EGF concentration, peripheral blood parameters and immunosenescence biomarkers. The proportion of CD8 + CD28- T cells, CD4+ and CD8+ T cells, CD4/CD8 ratio and CD19+ B cells. The 33 patients with complete information were included. The predictive causal information (PCI) was calculated for all possible models. The model with a minimum number of predictors, but with high prediction accuracy (PCI>0.7) was selected. Good, rare and poor responder patients were identified using the predictive probability of treatment success. Results: The mean of PCI increased from 0.486, when only one predictor is considered, to 0.98 using the multivariate approach with all predictors. The model considering the proportion of CD4+ T cell, basal Epidermal Growth Factor (EGF) concentration, neutrophil to lymphocyte ratio, Monocytes, and Neutrophils as predictors were selected (PCI>0.74). Patients predicted as good responders according to the pre-treatment biomarkers values treated with CIMAvax-EGF had a significant higher observed survival compared with the control group (p=0.03). No difference was observed for bad responders. Conclusions: Peripheral blood parameters and immunosenescence biomarkers together with basal EGF concentration in serum resulted in good predictors of the CIMAvax-EGF success in advanced NSCLC. Future research should explore molecular and genetic profile as biomarkers for CIMAvax-EGF and it combination with immune-checkpoint inhibitors. The study illustrates the application of a new methodology, based on causal inference, to evaluate multivariate pre-treatment predictors. The multivariate approach allows realistic predictions of the clinical benefit of patients and should be introduced in daily clinical practice.

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Differential effects of two therapeutic cancer vaccines on short- and long-term survival populations among patients with advanced lung cancer

Abstract: Differential effects of two therapeutic cancer vaccines on short-and long-term survival populations among patients with advanced lung cancer, Seminars in Oncology,

Cited by 10 publications

References 18 publications

Epitope targeting with self-assembled peptide vaccines

Epitope targeting with self-assembled peptide vaccines

Identifying predictive biomarkers of CIMAvaxEGF success in non–small cell lung cancer patients

Identifying predictive biomarkers of CIMAvaxEGF success in Non–Small Cell Lung Cancer Patients.

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