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Integrative analysis of two cell lines derived from a non-small-lung cancer patient - a panomics approach.
|Title||Integrative analysis of two cell lines derived from a non-small-lung cancer patient - a panomics approach.|
|Publication Type||Journal Article|
|Year of Publication||2014|
|Authors||Mayba O, Gnad F, Peyton M, Zhang F, Walter K, DU P, Huntley MA, Jiang Z, Liu J, Haverty PM, Gentleman RC, Li R, Minna JD, Li Y, Shames DS, Zhang Z|
|Journal||Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|
Cancer cells derived from different stages of tumor progression may exhibit distinct biological properties, as exemplified by the paired lung cancer cell lines H1993 and H2073. While H1993 was derived from chemo-naive metastasized tumor, H2073 originated from the chemo-resistant primary tumor from the same patient and exhibits strikingly different drug response profile. To understand the underlying genetic and epigenetic bases for their biological properties, we investigated these cells using a wide range of large-scale methods including whole genome sequencing, RNA sequencing, SNP array, DNA methylation array, and de novo genome assembly. We conducted an integrative analysis of both cell lines to distinguish between potential driver and passenger alterations. Although many genes are mutated in these cell lines, the combination of DNA- and RNA-based variant information strongly implicates a small number of genes including TP53 and STK11 as likely drivers. Likewise, we found a diverse set of genes differentially expressed between these cell lines, but only a fraction can be attributed to changes in DNA copy number or methylation. This set included the ABC transporter ABCC4, implicated in drug resistance, and the metastasis associated MET oncogene. While the rich data content allowed us to reduce the space of hypotheses that could explain most of the observed biological properties, we also caution there is a lack of statistical power and inherent limitations in such single patient case studies.
|Alternate Journal||Pac Symp Biocomput|