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Lung cancer is a heterogeneous disease in which patient-specific treatments are desirable and the development of targeted therapies has been effective. Although mutations in KRAS are frequent in lung adenocarcinoma, there are currently no targeted agents against KRAS. Using a mouse lung adenocarcinoma cell line with a Kras mutation (CMT167), we previously showed that PPARγ activation in lung cancer cells inhibits cell growth in vitro yet promotes tumor progression when activated in myeloid cells of the tumor microenvironment. Here, we report that PPARγ activation in myeloid cells promotes the production of TGFβ1, which, in turn, acts on CMT167 cancer cells to increase migration and induce an epithelial–mesenchymal transition (EMT). Targeting TGFβ1 signaling in CMT167 cells prevented their growth and metastasis in vivo. Similarly, another mouse lung adenocarcinoma cell line with a Kras mutation, LLC, induced TGFβ1 in myeloid cells through PPARγ activation. However, LLC cells are more mesenchymal and did not undergo EMT in response to TGFβ1, nor did LLC require TGFβ1 signaling for metastasis in vivo. Converting CMT167 cells to a mesenchymal phenotype through overexpression of ZEB1 made them unresponsive to TGFβ1 receptor inhibition. The ability of TGFβ1 to induce EMT in lung tumors may represent a critical process in cancer progression. We propose that TGFβ receptor inhibition could provide an additional treatment option for KRAS-mutant epithelial lung tumors.Implications: This study suggests that TGFβ receptor inhibitors may be an effective therapy in a subset of KRAS-mutant patients with non–small cell lung cancer, which show an epithelial phenotype.

S1: Differentiation state of CMT-luc and LLC-luc cells. S2: Intratumoral myeloid cell populations do not change with PPARγ knockout or activation. S3: TGFβRII knockdown CMT-luc cells are less responsive to TGF-β1 S4: Loss of PPARγ in myeloid cells does not affect LLC-luc tumor progression. S5: LLC cell response to TGF-β1 treatment.

Terminology definitions as used by the Precision Oncology Decision Support (PODS) team at MD Anderson Cancer Center

Supplementary Table S1. FDA approved HER2-targeted therapies

This shows the efficiency of immuodepletion experiments

Prominent commercial vendors providing decision support services (as of November 1, 2017)

The complement cascade is a part of the innate immune system that acts primarily to remove pathogens and injured cells. However, complement activation is also peculiarly associated with tumor progression. Here we report mechanistic insights into this association in multiple immunocompetent orthotopic models of lung cancer. After tumor engraftment, we observed systemic activation of the complement cascade as reflected by elevated levels of the key regulator C3a. Notably, growth of primary tumors and metastases was both strongly inhibited in C3-deficient mice (C3−/− mice), with tumors undetectable in many subjects. Growth inhibition was associated with increased numbers of IFNγ+/TNFα+/IL10+ CD4+ and CD8+ T cells. Immunodepletion of CD4+ but not CD8+ T cells in tumor-bearing subjects reversed the inhibitory effects of C3 deletion. Similarly, antagonists of the C3a or C5a receptors inhibited tumor growth. Investigations using multiple tumor cell lines in the orthotopic model suggested the involvement of a C3/C3 receptor autocrine signaling loop in regulating tumor growth. Overall, our findings offer functional evidence that complement activation serves as a critical immunomodulator in lung cancer progression, acting to drive immune escape via a C3/C5–dependent pathway.Significance: This provocative study suggests that inhibiting complement activation may heighten immunotherapeutic responses in lung cancer, offering findings with immediate implications, given the existing clinical availability of complement antagonists. Cancer Res; 78(1); 143–56. ©2017 AACR.

With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719–31. ©2018 AACR.

These figures show experiments of tumor growth in Factor B-/- mice. They also show gating strategy for flow cytometry and changes in inflammatory cells. Data showing loss of CIITA in cancer cells alters the response to complement depletion.

Actionable gene list for the Precision Oncology Decision Support (PODS) team at MD Anderson Cancer Center (as of November 1, 2017)

A peptide sequencing scheme utilizing fluorescence microscopy and Edman degradation to determine the amino acid position in fluorophore-labeled peptides was recently reported, referred to as fluorosequencing. It was observed that multiple fluorophores covalently linked to a peptide scaffold resulted in a decrease in the anticipated fluorescence output and worsened the single-molecule fluorescence analysis. In this study, we report an improvement in the photophysical properties of fluorophore-labeled peptides by incorporating long and flexible (PEG)(10) linkers at the peptide attachment points. Long linkers to the fluorophores were installed using copper-catalyzed azide-alkyne cycloaddition conditions. The photophysical properties of these peptides were analyzed in solution and immobilized on a microscope slide at the single-molecule level under peptide fluorosequencing conditions. Solution-phase fluorescence analysis showed improvements in both quantum yield and fluorescence lifetime with the long linkers. While on the solid support, photometry measurements showed significant increases in fluorescence brightness and 20 to 60% improvements in the ability to determine the amino acid position with fluorosequencing. This spatial distancing strategy demonstrates improvements in the peptide sequencing platform and provides a general approach for improving the photophysical properties in fluorophore-labeled macromolecules.

Objective: Multiplex immunohistochemistry (mIHC) and multiplexed ion beam imaging (MIBI) images are usually phenotyped using a manual thresholding process. The thresholding is prone to biases, especially when examining multiple images with high cellularity. Results: Unsupervised cell phenotyping methods including PhenoGraph, flowMeans, and SamSPECTRAL, primarily used in flow cytometry data, often perform poorly or need elaborate tuning to perform well in the context of mIHC and MIBI data. We show that, instead, semi-supervised cell clustering using Random Forests, linear and quadratic discriminant analysis are superior. We test the performance of the methods on two mIHC datasets from the University of Colorado School of Medicine and a publicly available MIBI dataset. Each dataset contains numerous highly complex images.

PurposeLung cancers bearing oncogenic EML4-ALK fusions respond to targeted tyrosine kinase inhibitors (TKIs; e.g. alectinib), with variation in the degree of shrinkage and duration of treatment (DOT). We previously demonstrated a positive association of a TKI-induced interferon gamma (IFNγ) transcriptional response with DOT in EGFR-mutant lung cancers. Herein, we used murine models of EML4-ALK lung cancer to test a role for host immunity in the therapeutic response to alectinib.Experimental DesignThree murine EML4-ALK cell lines (EA1, EA2, EA3) were implanted orthotopically into the lungs of immunocompetent and immunodeficient mice and treated with alectinib. Tumor volumes were serially measured by μCT. Immune cell content was measured by flow cytometry, multispectral immunofluorescence and CyTOF. Transcriptional responses to alectinib were assessed by RNAseq and secreted chemokines were measured by ELISA.ResultsAll cell lines were sensitive to alectinib in vitro. EA1 and EA3 tumors retained residual disease that rapidly progressed upon termination of treatment while EA2 tumors were eliminated by TKI treatment. Alectinib induced inflammatory transcriptional programs and multiple chemokines in all cell lines while untreated tumors exhibited distinct baseline chemokine expression patterns and content of CD8+ T cells and myeloid subsets. When propagated in immune-deficient mice, all three cell line-derived lung tumor models exhibited significant shrinkage followed by prompt progression despite continuous alectinib treatment.ConclusionsThe findings support an hypothesis that host and TKI-stimulated production of chemokines by tumor cells promotes functional engagement of adaptive immune cells within the tumor microenvironment that enhances the durability and depth of TKI response.Statement of Translational RelevancePatients with metastatic lung cancer harboring ALK fusions are treated with targeted tyrosine kinase inhibitors (TKI) in the first line setting. Despite bearing the same driver oncogene, patients experience a range of tumor burden reduction and variable amounts of residual disease. Residual disease burden associates with patient survival and contributes to the emergence of drug resistance yielding treatment failure. The factors mediating this differential response to TKI and residual disease are incompletely understood. Our group has developed a panel of murine ALK driven lung cancer cell lines that reproducibly show differences in the depth and duration of response when implanted into immunocompetent mice. Data using this model indicate that the presence of CD8+ T cells is a major contributor to the depth and duration of response. These models will be critical in developing rational combination therapies to augment the immune microenvironment engagement along with TKIs to improve outcomes for these patients.