EGFR Tyrosine Kinase Inhibitors for the Treatment of Metastatic Non-Small Cell Lung Cancer Harboring Uncommon EGFR Mutations: A Podcast.

Supplementary file1 (MP4 21169 KB).

Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer.

Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns-an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular distances, we can identify four groups related to inflamed and not-inflamed tumors. Cellular distribution patterns and distance are associated with survival in univariate and multivariable analyses. Spatial distribution is a tool to better understand the tumor microenvironment, predict outcomes, and may can help select therapeutic interventions.

Integrative proteomic and transcriptomic analysis provides evidence for TrkB (NTRK2) as a therapeutic target in combination with tyrosine kinase inhibitors for non-small cell lung cancer.

While several molecular targets have been identified for adenocarcinoma (ACA) of the lung, similar drivers with squamous cell carcinoma (SCC) are sparse. We compared signaling pathways and potential therapeutic targets in lung SCC and ACA tumors using reverse phase proteomic arrays (RPPA) from two independent cohorts of resected early stage NSCLC patients: a testing set using an MDACC cohort (N=140) and a validation set using the Cancer Genome Atlas (TCGA) cohorts. We identified multiple potentially targetable proteins upregulated in SCC, including NRF2, Keap1, PARP, TrkB, and Chk2. Of these potential targets, we found that TrkB also had significant increases in gene expression in SCC as compared to adenocarcinoma. Thus, we next validated the upregulation of TrkB both in vitro and in vivo and found that it was constitutively expressed at high levels in a subset of SCC cell lines. Furthermore, we found that TrkB inhibition suppressed tumor growth, invasiveness and sensitized SCC cells to tyrosine kinase EGFR inhibition in a cell-specific manner.

Immunohistochemical and Image Analysis-Based Study Shows That Several Immune Checkpoints are Co-expressed in Non-Small Cell Lung Carcinoma Tumors.

INTRODUCTION: The understanding of immune checkpoint molecules' co-expression in non-small cell lung carcinoma (NCLC) is important to potentially design combinatorial immunotherapy approaches. METHODS: We studied 225 formalin-fixed, paraffin-embedded tumor tissues from stage I-III NCLCs - 142 adenocarcinomas (ADCs) and 83 squamous cell carcinomas (SCCs) - placed in tissue microarrays. Nine immune checkpoint markers were evaluated; four (programmed death ligand 1 [PD-L1], B7-H3, B7-H4, and indoleamine 2,3-dioxygenase 1 [IDO-1]) expressed predominantly in malignant cells (MCs) and five (inducible T cell costimulator, V-set immunoregulatory receptor, T-cell immunoglobulin mucin family member 3, lymphocyte activating 3, and OX40) expressed mostly in stromal tumor-associated inflammatory cells (TAICs). All markers were examined using a quantitative image analysis and correlated with clinicopathologic features, TAICs, and molecular characteristics. RESULTS: Using above the median value as positive expression in MCs and high density of TAICs expressing those markers, we identified higher expression of immune checkpoints in SCC than ADC. Common simultaneous expression by MCs was PD-L1 + B7-H3 + IDO-1 in ADC and PD-L1 + B7-H3, or B7-H3 + B7-H4, in SCC. TAICs expressing checkpoint were significantly higher in current smokers than in never smokers. Almost all the immune checkpoint markers showed positive correlation with TAICs expressing inflammatory cell markers. KRAS-mutant ADC specimens showed higher expression of PD-L1 in MCs and of B7-H3, T-cell immunoglobulin mucin family member 3, and IDO-1 in TAICs than wild type. Kaplan-Meier survival curves showed worse prognosis in ADC patients with higher B7-H4 expression by MCs. CONCLUSIONS: We found frequent immunohistochemical co-expression of immune checkpoints in surgically resected NCLC tumors and correlated with tumor histology, smoking history, tumor size, and the density of inflammatory cells and tumor mutational status.

Selecting Reliable mRNA Expression Measurements Across Platforms Improves Downstream Analysis.

With increasing use of publicly available gene expression data sets, the quality of the expression data is a critical issue for downstream analysis, gene signature development, and cross-validation of data sets. Thus, identifying reliable expression measurements by leveraging multiple mRNA expression platforms is an important analytical task. In this study, we propose a statistical framework for selecting reliable measurements between platforms by modeling the correlations of mRNA expression levels using a beta-mixture model. The model-based selection provides an effective and objective way to separate good probes from probes with low quality, thereby improving the efficiency and accuracy of the analysis. The proposed method can be used to compare two microarray technologies or microarray and RNA sequencing measurements. We tested the approach in two matched profiling data sets, using microarray gene expression measurements from the same samples profiled on both Affymetrix and Illumina platforms. We also applied the algorithm to mRNA expression data to compare Affymetrix microarray data with RNA sequencing measurements. The algorithm successfully identified probes/genes with reliable measurements. Removing the unreliable measurements resulted in significant improvements for gene signature development and functional annotations.

In Vivo Delivery of miR-34a Sensitizes Lung Tumors to Radiation Through RAD51 Regulation.

MiR-34a, an important tumor-suppressing microRNA, is downregulated in several types of cancer; loss of its expression has been linked with unfavorable clinical outcomes in non-small-cell lung cancer (NSCLC), among others. MiR-34a represses several key oncogenic proteins, and a synthetic mimic of miR-34a is currently being tested in a cancer trial. However, little is known about the potential role of miR-34a in regulating DNA damage response and repair. Here, we demonstrate that miR-34a directly binds to the 3' untranslated region of RAD51 and regulates homologous recombination, inhibiting double-strand-break repair in NSCLC cells. We further demonstrate the therapeutic potential of miR-34a delivery in combination with radiotherapy in mouse models of lung cancer. Collectively, our results suggest that administration of miR-34a in combination with radiotherapy may represent a novel strategy for treating NSCLC.