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. 2008 Mar 4;105(9):3521-6.
doi: 10.1073/pnas.0712399105. Epub 2008 Feb 26.

Transcriptome sequencing of malignant pleural mesothelioma tumors

David J Sugarbaker  1 , William G Richards, Gavin J Gordon, Lingsheng Dong, Assunta De Rienzo, Gautam Maulik, Jonathan N Glickman, Lucian R Chirieac, Mor-Li Hartman, Bruce E Taillon, Lei Du, Pascal Bouffard, Stephen F Kingsmore, Neil A Miller, Andrew D Farmer, Roderick V Jensen, Steven R Gullans, Raphael Bueno
Affiliations

Transcriptome sequencing of malignant pleural mesothelioma tumors

David J Sugarbaker et al. Proc Natl Acad Sci U S A. .

Abstract

Cancers arise by the gradual accumulation of mutations in multiple genes. We now use shotgun pyrosequencing to characterize RNA mutations and expression levels unique to malignant pleural mesotheliomas (MPMs) and not present in control tissues. On average, 266 Mb of cDNA were sequenced from each of four MPMs, from a control pulmonary adenocarcinoma (ADCA), and from normal lung tissue. Previously observed differences in MPM RNA expression levels were confirmed. Point mutations were identified by using criteria that require the presence of the mutation in at least four reads and in both cDNA strands and the absence of the mutation from sequence databases, normal adjacent tissues, and other controls. In the four MPMs, 15 nonsynonymous mutations were discovered: 7 were point mutations, 3 were deletions, 4 were exclusively expressed as a consequence of imputed epigenetic silencing, and 1 was putatively expressed as a consequence of RNA editing. Notably, each MPM had a different mutation profile, and no mutated gene was previously implicated in MPM. Of the seven point mutations, three were observed in at least one tumor from 49 other MPM patients. The mutations were in genes that could be causally related to cancer and included XRCC6, PDZK1IP1, ACTR1A, and AVEN.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Transcriptome characteristics. (A) Number of Known RefSeq Genes detected by at least 1 read (solid lines) and 20 reads (dashed lines) as a function of increasing depth of transcriptome sequencing (i.e., Number of Reads) for the six patient specimens. The horizontal asymptote represents ≈17,000 of the Known RefSeq Genes detected by at least one read in any of the four MPM samples, which encompassed a total of 7 million reads. (B) Classification of tumor specimens using read counts to calculate gene expression ratios for six known diagnostic genes and their geometric mean (23). Ratios correctly identified each tumor type (i.e., >1, MPM; <1, ADCA). (C) Analysis of percentage of reads containing known coding region SNVs in the six tissue samples. Known variants were selected based on >16 reads of coverage in the region of interest (see SI Table 6 for data). The distribution of reads ≈50% showing heterozygous expression of the variant is consistent with a binomial distribution.
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