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Multiparametric profiling of non-small-cell lung cancers reveals distinct immunophenotypes.

ABSTRACT: BACKGROUND. Immune checkpoint blockade improves survival in a subset of patients with non-small-cell lung cancer (NSCLC), but robust biomarkers that predict response to PD-1 pathway inhibitors are lacking. Furthermore, our understanding of the diversity of the NSCLC tumor immune microenvironment remains limited. METHODS. We performed comprehensive flow cytometric immunoprofiling on both tumor and immune cells from 51 NSCLCs and integrated this analysis with clinical and histopathologic characteristics, next-generation sequencing, mRNA expression, and PD-L1 immunohistochemistry (IHC). RESULTS. Cytometric profiling identified an immunologically "hot" cluster with abundant CD8⁺ T cells expressing high levels of PD-1 and TIM-3 and an immunologically "cold" cluster with lower relative abundance of CD8⁺ T cells and expression of inhibitory markers. The "hot" cluster was highly enriched for expression of genes associated with T cell trafficking and cytotoxic function and high PD-L1 expression by IHC. There was no correlation between immunophenotype and KRAS or EGFR mutation, or patient smoking history, but we did observe an enrichment of squamous subtype and tumors with higher mutation burden in the "hot" cluster. Additionally, approximately 20% of cases had high B cell infiltrates with a subset producing IL-10. CONCLUSIONS. Our results support the use of immune-based metrics to study response and resistance to immunotherapy in lung cancer. FUNDING. The Robert A. and Renée E. Belfer Family Foundation, Expect Miracles Foundation, Starr Cancer Consortium, Stand Up to Cancer Foundation, Conquer Cancer Foundation, International Association for the Study of Lung Cancer, National Cancer Institute (R01 CA205150), and the Damon Runyon Cancer Research Foundation.

SUBMITTER: Lizotte PH

PROVIDER: S-EPMC5033841 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Multiparametric profiling of non-small-cell lung cancers reveals distinct immunophenotypes.

Lizotte Patrick H PH Ivanova Elena V EV Awad Mark M MM Jones Robert E RE Keogh Lauren L Liu Hongye H Dries Ruben R Almonte Christina C Herter-Sprie Grit S GS Santos Abigail A Feeney Nora B NB Paweletz Cloud P CP Kulkarni Meghana M MM Bass Adam J AJ Rustgi Anil K AK Yuan Guo-Cheng GC Kufe Donald W DW Jänne Pasi A PA Hammerman Peter S PS Sholl Lynette M LM Hodi F Stephen FS Richards William G WG Bueno Raphael R English Jessie M JM Bittinger Mark A MA Wong Kwok-Kin KK

JCI insight 20160908 14

<b>BACKGROUND.</b> Immune checkpoint blockade improves survival in a subset of patients with non-small-cell lung cancer (NSCLC), but robust biomarkers that predict response to PD-1 pathway inhibitors are lacking. Furthermore, our understanding of the diversity of the NSCLC tumor immune microenvironment remains limited. <b>METHODS.</b> We performed comprehensive flow cytometric immunoprofiling on both tumor and immune cells from 51 NSCLCs and integrated this analysis with clinical and histopathol ...[more]

PMID: 27699239

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Project description:Background: Immune checkpoint blockade improves survival in a subset of patients with non-small cell lung cancer (NSCLC), but robust biomarkers that predict response to PD-1 pathway inhibitors are lacking. Furthermore, our understanding of the diversity of the NSCLC tumor immune microenvironment remains limited. Methods: We performed comprehensive flow-cytometric immunoprofiling on both tumor and immune cells from 51 NSCLCs and integrated this analysis with clinical and histopathologic characteristics, next generation sequencing, mRNA expression, and PD-L1 immunohistochemistry (IHC). Results: Cytometric profiling identified an immunologically “hot” cluster with abundant CD8+ T cells expressing high levels of the PD-1 and TIM-3, and an immunologically “cold” cluster with lower relative abundance of CD8+ T cells and expression of inhibitory markers. The “hot” cluster was highly enriched for expression of genes associated with T cell trafficking and cytotoxic function, and high PD-L1 expression by IHC. There was no correlation between immunophenotype and KRAS or EGFR mutation, or patient smoking history, but we did observe an enrichment of squamous subtype and tumors with higher mutation burden in the “hot” cluster. Additionally, ~20% of cases had high B cell infiltrates with a subset producing IL-10. Conclusions: Our results support the use of immune-based metrics to study response and resistance to immunotherapy in lung cancer. Background: Immune checkpoint blockade improves survival in a subset of patients with non-small cell lung cancer (NSCLC), but robust biomarkers that predict response to PD-1 pathway inhibitors are lacking. Furthermore, our understanding of the diversity of the NSCLC tumor immune microenvironment remains limited. Methods: We performed comprehensive flow-cytometric immunoprofiling on both tumor and immune cells from 51 NSCLCs and integrated this analysis with clinical and histopathologic characteristics, next generation sequencing, mRNA expression, and PD-L1 immunohistochemistry (IHC). Results: Cytometric profiling identified an immunologically “hot” cluster with abundant CD8+ T cells expressing high levels of the PD-1 and TIM-3, and an immunologically “cold” cluster with lower relative abundance of CD8+ T cells and expression of inhibitory markers. The “hot” cluster was highly enriched for expression of genes associated with T cell trafficking and cytotoxic function, and high PD-L1 expression by IHC. There was no correlation between immunophenotype and KRAS or EGFR mutation, or patient smoking history, but we did observe an enrichment of squamous subtype and tumors with higher mutation burden in the “hot” cluster. Additionally, ~20% of cases had high B cell infiltrates with a subset producing IL-10. Conclusions: Our results support the use of immune-based metrics to study response and resistance to immunotherapy in lung cancer. 29 NSCLC cases analyzed wth Nanostring human PanCancer immune module

Project description:BackgroundThe testing for capability of some routine blood test parameters to reflect the biology of non-small cell lung carcinoma with different driver mutations is of great interest and practice significance. We aim to screen these variables and, if allowed, develop a novel predictive model based on results of these routine blood tests commonly performed in clinical practice to inform which can help doctors assess the patient's genetic mutation status as early as possible before surgery.MethodsFor the exploration cohort, we included 1,595 patients who were diagnosed with non-small cell lung cancer (NSCLC) and genetically profiled by a next-generation sequencing panel in the First Affiliated Hospital of Guangzhou Medical University. The external validation cohort, which consists of 197 NSCLC cancer patients from Sun Yat-sen University Cancer Hospital, was subsequently established.ResultsWe analyzed the association between 46 frequently tested laboratory variables and different genetic mutation types. KRAS mutation was found to be a unique subtype that exclusively correlated with several blood parameters in our study. Least absolute shrinkage and selection operator (LASSO) regression was performed, and the following parameters were found to be significantly associated with KRAS mutation: triglycerides [odds ratio (OR) =1.63], arterial oxygen partial pressure (OR =0.97), uric acid (OR =1.01), basophil count (OR =1.41), eosinophil count (OR =1.146), fibrinogen (OR =1.42), standard bicarbonate (OR =0.85), high-density lipoprotein cholesterol (OR =0.18), alpha-L-fucosidase (OR =1.07). The areas under the receiver-operator characteristic curve in the training set and the external validation set were 0.85 [95% confidence interval (CI): 0.81-0.88] and 0.81 (95% CI: 0.71-0.91), respectively.ConclusionsWe developed a non-invasive, more cost-effective predictive model of NSCLC based on routinely available variables, with practical predictive power. This model can be used as a practical screening tool to guide the use of more specialized and expensive molecular assays for KRAS mutation in NSCLC. However, further studies are warranted to investigate the mechanism underlying such association between KRAS mutations and the related parameters of blood tests.

Project description:BackgroundNon-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC.MethodsComparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC.ResultsAt DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1 and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of ~800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944.ConclusionsIntegrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes.

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Multiparametric profiling of non-small-cell lung cancers reveals distinct immunophenotypes.

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Multiparametric profiling of non-small-cell lung cancers reveals distinct immunophenotypes.

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