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1.
BMC Cancer ; 18(1): 87, 2018 01 22.
Artigo em Inglês | MEDLINE | ID: mdl-29357823

RESUMO

BACKGROUND: Patients with highly mutated tumors, such as melanoma or smoking-related lung cancer, have higher rates of response to immune checkpoint blockade therapy, perhaps due to increased neoantigen expression. Many chemotherapies including platinum compounds are known to be mutagenic, but the impact of standard treatment protocols on mutational burden and resulting neoantigen expression in most human cancers is unknown. METHODS: We sought to quantify the effect of chemotherapy treatment on computationally predicted neoantigen expression for high grade serous ovarian carcinoma patients enrolled in the Australian Ovarian Cancer Study. In this series, 35 of 114 samples were collected after exposure to chemotherapy; 14 are matched with an untreated sample from the same patient. Our approach integrates whole genome and RNA sequencing of bulk tumor samples with class I MHC binding prediction and mutational signatures extracted from studies of chemotherapy-exposed Caenorhabditis elegans and Gallus gallus cells. We additionally investigated the relationship between neoantigens, tumor infiltrating immune cells estimated from RNA-seq with CIBERSORT, and patient survival. RESULTS: Greater neoantigen burden and CD8+ T cell infiltration in primary, pre-treatment samples were independently associated with improved survival. Relapse samples collected after chemotherapy harbored a median of 78% more expressed neoantigens than untreated primary samples, a figure that combines the effects of chemotherapy and other processes operative during relapse. The contribution from chemotherapy-associated signatures was small, accounting for a mean of 5% (range 0-16) of the expressed neoantigen burden in relapse samples. In both treated and untreated samples, most neoantigens were attributed to COSMIC Signature (3), associated with BRCA disruption, Signature (1), associated with a slow mutagenic process active in healthy tissue, and Signature (8), of unknown etiology. CONCLUSION: Relapsed ovarian cancers harbor more predicted neoantigens than primary tumors, but the increase is due to pre-existing mutational processes, not mutagenesis from chemotherapy.


Assuntos
Antígenos de Neoplasias/genética , Recidiva Local de Neoplasia/tratamento farmacológico , Recidiva Local de Neoplasia/imunologia , Neoplasias Ovarianas/tratamento farmacológico , Neoplasias Ovarianas/imunologia , Idoso , Animais , Antígenos de Neoplasias/imunologia , Linfócitos T CD8-Positivos/imunologia , Linfócitos T CD8-Positivos/patologia , Caenorhabditis elegans/efeitos dos fármacos , Caenorhabditis elegans/genética , Galinhas/genética , Feminino , Regulação Neoplásica da Expressão Gênica , Genoma , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Macrófagos/efeitos dos fármacos , Macrófagos/imunologia , Pessoa de Meia-Idade , Mutação , Recidiva Local de Neoplasia/genética , Recidiva Local de Neoplasia/patologia , Células-Tronco Neoplásicas/efeitos dos fármacos , Células-Tronco Neoplásicas/imunologia , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/patologia , Platina/efeitos adversos
2.
Bioinformatics ; 32(15): 2378-9, 2016 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-27153605

RESUMO

UNLABELLED: P: ileup.js is a new browser-based genome viewer. It is designed to facilitate the investigation of evidence for genomic variants within larger web applications. It takes advantage of recent developments in the JavaScript ecosystem to provide a modular, reliable and easily embedded library. AVAILABILITY AND IMPLEMENTATION: The code and documentation for pileup.js is publicly available at https://github.com/hammerlab/pileup.js under the Apache 2.0 license. CONTACT: correspondence@hammerlab.org.


Assuntos
Gráficos por Computador , Genômica , Software , Genoma , Internet , Linguagens de Programação
3.
Cell Rep ; 25(13): 3721-3732.e6, 2018 12 26.
Artigo em Inglês | MEDLINE | ID: mdl-30590044

RESUMO

Complement-mediated cytotoxicity may act as a selective pressure for tumor overexpression of complement regulators. We hypothesize that the same selective pressure could lead to complement alterations at the genetic level. We find that, when analyzed as a pathway, mutations in complement genes occur at a relatively high frequency and are associated with changes in overall survival across a number of cancer types. Analysis of pathways expressed in patients with complement mutations that are associated with poor overall survival reveals crosstalk between complement and hypoxia in colorectal cancer. The importance of this crosstalk is highlighted by two key findings: hypoxic signaling is increased in tumors harboring complement mutations, and hypoxic tumor cells are resistant to complement-mediated cytotoxicity due, in part, to hypoxia-induced expression of complement regulator CD55. The range of strategies employed by tumors to dysregulate the complement system testifies to the importance of this pathway in tumor progression.


Assuntos
Neoplasias Colorretais/genética , Neoplasias Colorretais/imunologia , Imunidade Inata/genética , Mutação/genética , Transdução de Sinais , Hipóxia Tumoral/genética , Adulto , Animais , Antígenos de Neoplasias/metabolismo , Neoplasias Colorretais/patologia , Proteínas do Sistema Complemento/genética , Citotoxicidade Imunológica/genética , Células HCT116 , Humanos , Masculino , Camundongos , Análise de Sobrevida
4.
Cancer Cell ; 29(1): 104-116, 2016 Jan 11.
Artigo em Inglês | MEDLINE | ID: mdl-26766592

RESUMO

Dysregulated metabolism is a hallmark of cancer, manifested through alterations in metabolites. We performed metabolomic profiling on 138 matched clear cell renal cell carcinoma (ccRCC)/normal tissue pairs and found that ccRCC is characterized by broad shifts in central carbon metabolism, one-carbon metabolism, and antioxidant response. Tumor progression and metastasis were associated with metabolite increases in glutathione and cysteine/methionine metabolism pathways. We develop an analytic pipeline and visualization tool (metabolograms) to bridge the gap between TCGA transcriptomic profiling and our metabolomic data, which enables us to assemble an integrated pathway-level metabolic atlas and to demonstrate discordance between transcriptome and metabolome. Lastly, expression profiling was performed on a high-glutathione cluster, which corresponds to a poor-survival subgroup in the ccRCC TCGA cohort.


Assuntos
Biomarcadores Tumorais/genética , Carcinoma de Células Renais/diagnóstico , Carcinoma de Células Renais/genética , Regulação Neoplásica da Expressão Gênica/genética , Neoplasias Renais/diagnóstico , Neoplasias Renais/genética , Perfilação da Expressão Gênica/métodos , Predisposição Genética para Doença/genética , Humanos , Metabolômica/métodos , Estadiamento de Neoplasias , Prognóstico
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