PURPOSE: Molecular profiling of alterations associated with lung cancer holds the promise to define clinical parameters such as response to treatment or survival. Because <5% of small cell lung cancers and <30% of non-small cell lung cancers are surgically resectable, molecular analysis will perforce rely on routinely available clinical samples such as biopsies. Identifying tumor mutations in such samples will require a sensitive and robust technology to overcome signal from excess amounts of normal DNA. EXPERIMENTAL DESIGN: p53 mutation status was assessed from the DNA and RNA of biopsies collected prospectively from 83 patients with lung cancer. Biopsies were obtained either by conventional bronchoscopy or computed tomography-guided percutaneous biopsy. Matched surgical specimens were available for 22 patients. Three assays were used: direct sequencing; a functional assay in yeast; and a newly developed PCR/ligase detection reaction/Universal DNA array assay. RESULTS: Using the functional assay, p53 mutation was found in 62% of biopsies and 64% of surgical specimens with a concordance of 80%. The sensitivity of the functional assay was determined to be 5%. Direct sequencing confirmed mutations in 92% of surgical specimens but in only 78% of biopsies. The DNA array confirmed 100% of mutations in both biopsies and surgical specimens. Using this newly developed DNA array, we demonstrate the feasibility of directly identifying p53 mutations in clinical samples containing <5% of tumor cells. CONCLUSIONS: The versatility and sensitivity of this new array assay should allow additional development of mutation profiling arrays that could be applied to biological samples with a low tumor cell content such as bronchial aspirates, bronchoalveolar lavage fluid, or serum.
PURPOSE: Molecular profiling of alterations associated with lung cancer holds the promise to define clinical parameters such as response to treatment or survival. Because <5% of small cell lung cancers and <30% of non-small cell lung cancers are surgically resectable, molecular analysis will perforce rely on routinely available clinical samples such as biopsies. Identifying tumor mutations in such samples will require a sensitive and robust technology to overcome signal from excess amounts of normal DNA. EXPERIMENTAL DESIGN:p53 mutation status was assessed from the DNA and RNA of biopsies collected prospectively from 83 patients with lung cancer. Biopsies were obtained either by conventional bronchoscopy or computed tomography-guided percutaneous biopsy. Matched surgical specimens were available for 22 patients. Three assays were used: direct sequencing; a functional assay in yeast; and a newly developed PCR/ligase detection reaction/Universal DNA array assay. RESULTS: Using the functional assay, p53 mutation was found in 62% of biopsies and 64% of surgical specimens with a concordance of 80%. The sensitivity of the functional assay was determined to be 5%. Direct sequencing confirmed mutations in 92% of surgical specimens but in only 78% of biopsies. The DNA array confirmed 100% of mutations in both biopsies and surgical specimens. Using this newly developed DNA array, we demonstrate the feasibility of directly identifying p53 mutations in clinical samples containing <5% of tumor cells. CONCLUSIONS: The versatility and sensitivity of this new array assay should allow additional development of mutation profiling arrays that could be applied to biological samples with a low tumor cell content such as bronchial aspirates, bronchoalveolar lavage fluid, or serum.
Authors: Jian Wu; Hanno Matthaei; Anirban Maitra; Marco Dal Molin; Laura D Wood; James R Eshleman; Michael Goggins; Marcia I Canto; Richard D Schulick; Barish H Edil; Christopher L Wolfgang; Alison P Klein; Luis A Diaz; Peter J Allen; C Max Schmidt; Kenneth W Kinzler; Nickolas Papadopoulos; Ralph H Hruban; Bert Vogelstein Journal: Sci Transl Med Date: 2011-07-20 Impact factor: 17.956
Authors: Hanna Pincas; Maneesh R Pingle; Jianmin Huang; Kaiqin Lao; Philip B Paty; Alan M Friedman; Francis Barany Journal: Nucleic Acids Res Date: 2004-10-28 Impact factor: 16.971
Authors: Hanno Matthaei; Jian Wu; Marco Dal Molin; Chanjuan Shi; Sven Perner; Glen Kristiansen; Philipp Lingohr; Jörg C Kalff; Christopher L Wolfgang; Kenneth W Kinzler; Bert Vogelstein; Anirban Maitra; Ralph H Hruban Journal: Am J Surg Pathol Date: 2014-03 Impact factor: 6.394
Authors: Hanno Matthaei; Jian Wu; Marco Dal Molin; Marija Debeljak; Philipp Lingohr; Nora Katabi; David S Klimstra; N Volkan Adsay; James R Eshleman; Richard D Schulick; Kenneth W Kinzler; Bert Vogelstein; Ralph H Hruban; Anirban Maitra Journal: HPB (Oxford) Date: 2012-06-18 Impact factor: 3.647
Authors: Nicola Ciancio; Maria Grazia Galasso; Raffaele Campisi; Laura Bivona; Marcello Migliore; Giuseppe U Di Maria Journal: Multidiscip Respir Med Date: 2012-09-14