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Vaccine and immune cell therapy in non-small cell lung cancer.

ABSTRACT: Despite new advances in therapeutics, lung cancer remains the first cause of mortality among different types of malignancies. To improve survival, different strategies have been developed such as chemotherapy combinations, targeted therapies and more recently immunotherapy. Immunotherapy is based on the capability of the immune system to differentiate cancer cells from normal cells to fight against the tumor. The two main checkpoint inhibitors that have been widely studied in non-small cell lung cancer (NSCLC) are PD-1/PD-L1 and CTLA-4. However, interactions between tumor and immune system are much more complex with several different elements that take part and probably many new interactions to be discovered and studied for a better comprehension of those pathways. Vaccines are part of the prophylaxis and of the treatment for different infectious diseases. For that reason, they have allowed us to improve global survival worldwide. This same idea can be used for cancer treatment. First reports in clinical trials that used therapeutic vaccines in NSCLC were discouraging, but currently vaccines have a new chance in cancer therapy with the identification of new targetable antigens, adjuvant treatments and most interestingly, the combination of vaccines with anti-PD-1/PD-L1 and anti-CTLA-4 drugs. The aim of this article is to describe the scientific evidence that has been reported for the different types of vaccines and their mechanisms of action in the fight against NSCLC tumors to improve disease control.

SUBMITTER: Oliveres H

PROVIDER: S-EPMC5994506 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Vaccine and immune cell therapy in non-small cell lung cancer.

Oliveres Helena H Caglevic Christian C Passiglia Francesco F Taverna Simona S Smits Evelien E Rolfo Christian C

Journal of thoracic disease 20180501 Suppl 13

Despite new advances in therapeutics, lung cancer remains the first cause of mortality among different types of malignancies. To improve survival, different strategies have been developed such as chemotherapy combinations, targeted therapies and more recently immunotherapy. Immunotherapy is based on the capability of the immune system to differentiate cancer cells from normal cells to fight against the tumor. The two main checkpoint inhibitors that have been widely studied in non-small cell lung ...[more]

PMID: 29951309

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Project description:BackgroundThe development of immune checkpoint inhibitors (ICIs) is a revolutionary milestone in the field of immune-oncology. However, the low response rate is the major problem of ICI treatment. The recent studies showed that response rate to single-agent programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibition in unselected non-small cell lung cancer (NSCLC) patients is 25% so that researchers defined several biomarkers to predict the response of immunotherapy in ICIs treatment. Common biomarkers like tumor mutational burden (TMB) and PD-L1 expression have several limitations, such as low accuracy and inadequately validated cutoff value.MethodsTwo published and an unpublished ICIs treatment NSCLC cohorts with 129 patients were collected and divided into a training cohort (n = 53), a validation cohort (n = 22), and two independent test cohorts (n = 34 and n = 20). We identified six immune-related pathways whose mutational status was significantly associated with overall survival after ICIs treatment. Then these pathways mutational status combined with TMB, PD-L1 expression and intratumor heterogeneity were incorporated to build a Bayesian-regularization neural networks (BRNN) model to predict the ICIs treatment response.ResultsWe firstly proved that TMB, PD-L1, and mutant-allele tumor heterogeneity (MATH) were independent biomarkers. The survival analysis of six immune-related pathways revealed the mutational status could distinguish overall survival after ICIs treatment. When predicting immunotherapy efficacy, the overall accuracy of area under curve (AUC) in validation cohort reaches 0.85, outperforming previous predictors in either sensitivity or specificity. And the AUC in two independent test cohorts reach 0.74 and 0.80.ConclusionWe developed a pathway-model that could predict the efficacy of ICIs in NSCLC patients. Our study made a significant contribution to solving the low prediction accuracy of immunotherapy of single biomarker. With the accumulation of larger data sets, further studies are warranted to refine the predictive performance of the approach.

Project description:Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death in the world. Immunological analysis of the tumor microenvironment (immunoscore) shows great promise for improved prognosis and prediction of response to immunotherapy. However, the exact immune cell composition in NSCLC remains unclear. Here, we used flow cytometry to characterize the immune infiltrate in NSCLC tumors, non-cancerous lung tissue, regional lymph node, and blood. The cellular identity of >95% of all CD45+ immune cells was determined. Thirteen distinct immune cell types were identified in NSCLC tumors. T cells dominated the lung cancer landscape (on average 47% of all CD45+ immune cells). CD4+ T cells were the most abundant T cell population (26%), closely followed by CD8+ T cells (22%). Double negative CD4-CD8- T cells represented a small fraction (1.4%). CD19+ B cells were the second most common immune cell type in NSCLC tumors (16%), and four different B cell sub-populations were identified. Macrophages and natural killer (NK) cells composed 4.7 and 4.5% of the immune cell infiltrate, respectively. Three types of dendritic cells (DCs) were identified (plasmacytoid DCs, CD1c+ DCs, and CD141+ DCs) which together represented 2.1% of all immune cells. Among granulocytes, neutrophils were frequent (8.6%) with a high patient-to-patient variability, while mast cells (1.4%), basophils (0.4%), and eosinophils (0.3%) were less common. Across the cohort of patients, only B cells showed a significantly higher representation in NSCLC tumors compared to the distal lung. In contrast, the percentages of macrophages and NK cells were lower in tumors than in non-cancerous lung tissue. Furthermore, the fraction of macrophages with high HLA-DR expression levels was higher in NSCLC tumors relative to distal lung tissue. To make the method readily accessible, antibody panels and flow cytometry gating strategy used to identify the various immune cells are described in detail. This work should represent a useful resource for the immunomonitoring of patients with NSCLC.

Project description:Blood-based biomarkers including systemic inflammation (SI) indicators or circulating factors (cytokines, chemokines, or growth factors) are associated with a poor prognosis for lung cancer patients. Collectively these biomarkers can predict the immune state of a patient. We wanted to define and compare the immune states of small cell and non-small cell lung cancer patients, in the hopes that the information gained could lead to overall improvements in patient care and outcomes. Specimens and data from 235 patients was utilized, 49 surgically resected non-small cell lung cancer (NSCLC) patients with no evidence of disease (DF), 135 advanced non-small cell lung cancer (NSCLC), 51 small cell lung cancer (SCLC). SI markers neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte (PLR), systemic inflammation index (SII), and systemic inflammation response index (SIRI) were determined from blood counts. Forty-seven plasma cytokines were measured using a multiplex bead-based assay. Progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan-Meier and Cox Proportional Hazards models. NSCLC patients had significantly high levels of SI markers than SCLC and DF patients, while NLR, PLR and SII were also higher in SCLC than DF patients. SI optimized marker values to differentiate SI value were; 6.04 (NLR), 320 (PLR), 1615 (SII), and 7.3 (SIRI). Elevated levels NLR (p<0.001), PLR (p<0.001), and SII (p = 0.018) were associated with a worse PFS and OS in NSCLC, while none of the markers were associated with PFS in SCLC patients. NSCLC patients with a poor outcome displayed heterogeneous immune states relative to systemic inflammation and circulating IL-6 markers. These groups could be distinguished based on the cytokines IL-8, TNFα, and IL-27. We identified heterogeneity of immune states in SCLC and NSCLC patients and in NSCLC patients with the poorest prognosis. This heterogeneity could be exploited to improve outcomes for these patients.

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Vaccine and immune cell therapy in non-small cell lung cancer.

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Vaccine and immune cell therapy in non-small cell lung cancer.

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