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Deciphering the genomic, epigenomic and transcriptomic landscapes of pre-invasive lung cancer lesions to determine prognosis II

ABSTRACT: Deciphering the genomic, epigenomic and transcriptomic landscapes of pre-invasive lung cancer lesions to determine prognosis II

PROVIDER: PRJNA422415 | ENA |

REPOSITORIES: ENA

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Project description:An evaluation of multifocal lesions from patients with in-transit extremity melanoma to determine if all lesions from a patient harbor homogeneous patterns of gene expression; Gene expression profiling studies can help guide treatment for cancer patients by providing tools in the form of gene-expression signatures to characterize a tumor in terms of underlying biology, predicted response to therapy, metastatic progression and/or recurrence. The utility of gene signatures for defining therapeutic strategies in the treatment of extremity in-transit melanoma will be dependent on the genetic relationship between the multifocal lesions typically present in this disease and the extent to which a single lesion is representative of residual tumor burden. Using microarray-based gene expression profiling we examined 43 in-transit melanoma lesions across 17 patients with multifocal disease to determine whether one lesion could accurately characterize the underlying biology and genetic profile of a patient's tumor. Principal component analysis, unsupervised hierarchical clustering, one-way analysis of variance (ANOVA) and gene signatures predictive of chemosensitivity and oncogenic pathway activation showed gene expression patterns to be highly similar (p-values: <0.006; average r = 0.979) between lesions from a single patient but to be significantly different across patients (p<0.05). These findings demonstrate that individual melanoma tumor nodules in patients with multifocal disease are genetically similar and a single lesion can be used to predict response to chemotherapy, evaluate the activation status of oncogenic signaling pathways and characterize other aspects of the biology of an individual patient's disease. These results will facilitate the utilization of gene expression profiling in clinical trials of targeted therapy in melanoma allowing for more rational identification of candidates for specific therapies. Experiment Overall Design: Gene expression profiles were obtained from 43 lesions across 17 patients and evaluated using several different algorithms to determine the degree of correlation across multifocal lesions and to evaluate patterns of gene expression that are different across patients

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Deciphering the genomic, epigenomic and transcriptomic landscapes of pre-invasive lung cancer lesions to determine prognosis II

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