22 research outputs found

    Characterizing genomic alterations in cancer by complementary functional associations.

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    Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes

    RNA expression and risk of venous thromboembolism in lung cancer

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    Abstract Background The propensity to develop venous thromboembolism (VTE) on the basis of individual tumor biological features remains unknown. Objectives We conducted a whole transcriptome RNA sequencing strategy, focusing on a single cancer type (lung cancer), to identify biomarkers of cancer‐associated VTE. Methods Twelve propensity‐matched patients, 6 each with or without VTE, were identified from a prospective institutional review board–approved registry at the Cleveland Clinic with available tissue from surgical excision of a primary lung mass between 2010 and 2015. Patients were propensity matched based on age, sex, race, history of prior cancer, date of cancer diagnosis, stage, histology, number of lines of chemotherapy, and length of follow‐up. RNA sequencing was performed on tumor tissue, and gene set enrichment analysis (GSEA) was performed on differentially expressed genes. Results We identified 1037 genes with differential expression. In patients with VTE, 869 genes were overexpressed and 168 were underexpressed compared to patients without VTE. Of these, 276 overexpressed and 35 underexpressed were significantly different (Q < 0.05). GSEA revealed upregulation of genes in complement, inflammation, and KRAS signaling pathways in tumors from patients with VTE. Conclusions These differentially expressed genes and associated pathways provide biologic insights into cancer‐associated VTE and may provide insignts to develop new risk stratification schemes, prevention, or treatment strategies

    Targeting the Epidermal Growth Factor Receptor in EGFR-Mutated Lung Cancer: Current and Emerging Therapies

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    Epidermal growth factor receptor-targeting tyrosine kinase inhibitors (EGFR TKIs) are the standard of care for patients with EGFR-mutated metastatic lung cancer. While EGFR TKIs have initially high response rates, inherent and acquired resistance constitute a major challenge to the longitudinal treatment. Ongoing work is aimed at understanding the molecular basis of these resistance mechanisms, with exciting new studies evaluating novel agents and combination therapies to improve control of tumors with all forms of EGFR mutation. In this review, we first provide a discussion of EGFR-mutated lung cancer and the efficacy of available EGFR TKIs in the clinical setting against both common and rare EGFR mutations. Second, we discuss common resistance mechanisms that lead to therapy failure during treatment with EGFR TKIs. Third, we review novel approaches aimed at improving outcomes and overcoming resistance to EGFR TKIs. Finally, we highlight recent breakthroughs in the use of EGFR TKIs in non-metastatic EGFR-mutated lung cancer

    Drug resistance profiling of a new triple negative breast cancer patient-derived xenograft model

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    Abstract Background Triple-negative breast cancer (TNBC) represents an aggressive subtype with limited therapeutic options. Experimental preclinical models that recapitulate their tumors of origin can accelerate target identification, thereby potentially improving therapeutic efficacy. Patient-derived xenografts (PDXs), due to their genomic and transcriptomic fidelity to the tumors from which they are derived, are poised to improve the preclinical testing of drug-target combinations in translational models. Despite the previous development of breast and TNBC PDX models, those derived from patients with demonstrated health-disparities are lacking. Methods We use an aggressive TNBC PDX model propagated in SCID/Beige mice that was established from an African-American woman, TU-BcX-2 K1, and assess its metastatic potential and drug sensitivities under distinct in vitro conditions. Cellular derivatives of the primary tumor or the PDX were grown in 2D culture conditions or grown in mammospheres 3D culture. Flow cytometry and fluorescence staining was used to quantify cancer stem cell-like populations. qRT-PCR was used to describe the mesenchymal gene signature of the tumor. The sensitivity of TU-BcX-2 K1-derived cells to anti-neoplastic oncology drugs was compared in adherent cells and mammospheres. Drug response was evaluated using a live/dead staining kit and crystal violet staining. Results TU-BcX-2 K1 has a low propensity for metastasis, reflects a mesenchymal state, and contains a large burden of cancer stem cells. We show that TU-BcX-2 K1 cells have differential responses to cytotoxic and targeted therapies in 2D compared to 3D culture conditions insofar as several drug classes conferred sensitivity in 2D but not in 3D culture, or cells grown as mammospheres. Conclusions Here we introduce a new TNBC PDX model and demonstrate the differences in evaluating drug sensitivity in adherent cells compared to mammosphere, or suspension, culture

    Integrative radiogenomic profiling of squamous cell lung cancer

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    Radiation therapy is one of the mainstays of anti-cancer treatment, but the relationship between the radiosensitivity of cancer cells and their genomic characteristics is not well defined. Here we report the development of a high-throughput platform for measuring radiation survival in vitro and its validation by comparison to conventional clonogenic radiation survival analysis. We combined results from this high-throughput assay with genomic parameters in cell lines from squamous cell lung carcinoma, which is standardly treated by radiation therapy, to identify parameters that predict radiation sensitivity. We confirmed that activation of NFE2L2, a frequent event in lung squamous cancers, correlates with radiation resistance. NFE2L2 knockdown conferred both growth arrest and radiation sensitivity in a cell line with NFE2L2 mutation but not in a wild type cell line. An expression-based, in silico screen nominated inhibitors of PI3K as NFE2L2 antagonists. We showed that the selective PI3K inhibitor, NVP-BKM120, both decreased NRF2 protein levels and sensitized NFE2L2 or KEAP1 mutant cells to radiation. To assess determinants of radiation sensitivity further, we combined results from this high-throughput assay with single-sample gene set enrichment analysis (ssGSEA) of gene expression data. The resulting analysis identified pathways implicated in cell survival, genotoxic stress, detoxification, and innate and adaptive immunity as key correlates of radiation sensitivity. The integrative, high-throughput approach shown here for large-scale profiling of radiation survival and genomic features of solid-tumor derived cell lines should facilitate tumor radiogenomics and the discovery of radiation sensitizers and protective agents
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