Functional Analysis of Somatic Mutations in Lung Cancer

Abstract

We have conducted functional investigations of somatic mutations in lung cancer, focusing on genes/allelic variants individually and also using high throughput combinatorial approaches. We have gained insights into the impact of somatic mutations inRBM10, MAP2K1, ERBB2, EGFR and a host of other oncogenes or tumor suppressor proteins, on the initiation and maintenance of lung cancer. Notably, we have revealed for the first time the mechanism by which amplifications in an enhancer region (a novel super-enhancer), upstream of the MYC promoter, drives carcinogenesis. During the course of this project, we have also developed novel in vitro and in vivo experimental and analytical approaches, including genome editing methods, to augment our own research capabilities and that of the broader scientific community. The significance of our findings lies in the fact that we have now gained valuable insights into the molecular mechanisms by which somatic mutations in lung cancerthat were previously detected by large-scale, genomics approaches and were of unknown significanceincite tumorigenesis. The next step would be to translate this knowledge to devising more effective and tumor-specific targeted therapies, to benefit lung cancer patients.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2015
Accession Number
AD1005796

Entities

People

  • Alice Berger
  • Aruna Ramachandran
  • Heidi Greulich
  • Hugh Gannon
  • Matthew Meyerson
  • Peter Choi
  • Xiaoyang Zhang

Organizations

  • Dana–Farber Cancer Institute

Tags

DTIC Thesaurus Topics

  • Amplification
  • Biology
  • Cancer
  • Cell Line
  • Cell Physiological Processes
  • Communities
  • Computational Biology
  • Data Sets
  • Gene Expression
  • Genetics
  • Health Services
  • Lung Cancer
  • Neoplasms
  • Proteins
  • Rna Sequence Analysis
  • Small Molecules
  • Therapy

Fields of Study

  • Biology

Readers

  • Molecular Genetics
  • Molecular and genetic basis of cancer.
  • Oncology and Biomarker-Based Cancer Detection.