The impact of targeting TRAF2 and NCK-interacting protein kinase (TNIK) on anti-tumor effect in small cell lung cancer

View full abstracthttps://openworks.mdanderson.org/leading-edge/1056/thumbnail.jp

Validating DLL3-targeting CAR T in small cell lung cancer

View full abstracthttps://openworks.mdanderson.org/leading-edge/1022/thumbnail.jp

A murine preclinical syngeneic transplantation model for breast cancer precision medicine

We previously demonstrated that altered activity of lysophosphatidic acid in murine mammary glands promotes tumorigenesis. We have now established and characterized a heterogeneous collection of mouse-derived syngeneic transplants (MDSTs) as preclinical platforms for the assessment of personalized pharmacological therapies. Detailed molecular and phenotypic analyses revealed that MDSTs are the most heterogeneous group of genetically engineered mouse models (GEMMs) of breast cancer yet observed. Response of MDSTs to trametinib, a mitogen-activated protein kinase (MAPK) kinase inhibitor, correlated with RAS/MAPK signaling activity, as expected from studies in xenografts and clinical trials providing validation of the utility of the model. Sensitivity of MDSTs to talazoparib, a poly(adenosine 5′-diphosphate–ribose) polymerase (PARP) inhibitor, was predicted by PARP1 protein levels and by a new PARP sensitivity predictor (PSP) score developed from integrated analysis of drug sensitivity data of human cell lines. PSP score–based classification of The Cancer Genome Atlas breast cancer suggested that a subset of patients with limited therapeutic options would be expected to benefit from PARP-targeted drugs. These results indicate that MDSTs are useful models for studies of targeted therapies, and propose novel potential biomarkers for identification of breast cancer patients likely to benefit from personalized pharmacological treatments

Nitric Oxide Synthase Inhibition Enhances the Antitumor Effect of Radiation in the Treatment of Squamous Carcinoma Xenografts

This study tests whether the nitric oxide synthase (NOS) inhibitor, NG-nitro-L-arginine (L-NNA), combines favorably with ionizing radiation (IR) in controlling squamous carcinoma tumor growth. Animals bearing FaDu and A431 xenografts were treated with L-NNA in the drinking water. IR exposure was 10 Gy for tumor growth and survival studies and 4 Gy for ex vivo clonogenic assays. Cryosections were examined immunohistochemically for markers of apoptosis and hypoxia. Blood flow was assayed by fluorescent microscopy of tissue cryosections after i.v. injection of fluorospheres. Orally administered L-NNA for 24 hrs reduces tumor blood flow by 80% (p<0.01). Within 24 hrs L-NNA treatment stopped tumor growth for at least 10 days before tumor growth again ensued. The growth arrest was in part due to increased cell killing since a combination of L-NNA and a single 4 Gy IR caused 82% tumor cell killing measured by an ex vivo clonogenic assay compared to 49% by L-NNA or 29% by IR alone. A Kaplan-Meyer analysis of animal survival revealed a distinct survival advantage for the combined treatment. Combining L-NNA and IR was also found to be at least as effective as a single i.p. dose of cisplatin plus IR. In contrast to the in vivo studies, exposure of cells to L-NNA in vitro was without effect on clonogenicity with or without IR. Western and immunochemical analysis of expression of a number of proteins involved in NO signaling indicated that L-NNA treatment enhanced arginase-2 expression and that this may represent vasculature remodeling and escape from NOS inhibition. For tumors such as head and neck squamous carcinomas that show only modest responses to inhibitors of specific angiogenic pathways, targeting NO-dependent pro-survival and angiogenic mechanisms in both tumor and supporting stromal cells may present a potential new strategy for tumor control

In vivo analysis of gain-of-function mutations in the Drosophila eag-encoded potassium ion channel

Neuronal Na+ and K+ channels elicit currents in opposing directions and thus have opposing effects on neuronal excitability. Mutations in genes encoding Na+ or K+ channels often interact genetically, leading either to phenotypic suppression or enhancement for genes with opposing or similar effects on excitability respectively. For example, the effects of mutations in Shaker (Sh), which encodes a K+ channel subunit, are suppressed by loss of function mutations in the Na+ channel structural gene para, but enhanced by loss of function mutations in a second K + channel encoded by eag. Here I characterize three novel mutations that suppress the effects of a Sh mutation on behavior and neuronal excitability. Recombination mapping localized the mutations to the eag locus, and I used sequence analysis to determine that two of the mutations are caused by a single amino acid substitution (G297E) in the S2-S3 linker of Eag. Because these novel eag mutations confer opposite phenotypes to eag loss of function mutations, I suggest that eag G297E causes an eag gain of function phenotype. I hypothesize that the G297E substitution may cause premature, prolonged or constitutive opening of the Eag channels by favoring the "unlocked" state of the channel. The third mutation has two amino acid substitutions in Eag (A259V and E762V) and may also be a gain of function allele of eag . Interestingly, these mutations appear to manifest their most obvious phenotypes under conditions that prolong the action potential

Integrated Approaches for the Use of Large Datasets to Identify Rational Therapies for the Treatment of Lung Cancers

The benefit and burden of contemporary techniques for the molecular characterization of samples is the vast amount of data generated. In the era of &#8220;big data&#8222;, it has become imperative that we develop multi-disciplinary teams combining scientists, clinicians, and data analysts. In this review, we discuss a number of approaches developed by our University of Texas MD Anderson Lung Cancer Multidisciplinary Program to process and utilize such large datasets with the goal of identifying rational therapeutic options for biomarker-driven patient subsets. Large integrated datasets such as the The Cancer Genome Atlas (TCGA) for patient samples and the Cancer Cell Line Encyclopedia (CCLE) for tumor derived cell lines include genomic, transcriptomic, methylation, miRNA, and proteomic profiling alongside clinical data. To best use these datasets to address urgent questions such as whether we can define molecular subtypes of disease with specific therapeutic vulnerabilities, to quantify states such as epithelial-to-mesenchymal transition that are associated with resistance to treatment, or to identify potential therapeutic agents in models of cancer that are resistant to standard treatments required the development of tools for systematic, unbiased high-throughput analysis. Together, such tools, used in a multi-disciplinary environment, can be leveraged to identify novel treatments for molecularly defined subsets of cancer patients, which can be easily and rapidly translated from benchtop to bedside