Validation of whole genome amplification for analysis of the p53 tumor suppressor gene in limited amounts of tumor samples.

Personalized cancer treatment requires molecular characterization of individual tumor biopsies. These samples are frequently only available in limited quantities hampering genomic analysis. Several whole genome amplification (WGA) protocols have been developed with reported varying representation of genomic regions post amplification. In this study we investigate region dropout using a φ29 polymerase based WGA approach. DNA from 123 lung cancers specimens and corresponding normal tissue were used and evaluated by Sanger sequencing of the p53 exons 5-8. To enable comparative analysis of this scarce material, WGA samples were compared with unamplified material using a pooling strategy of the 123 samples. In addition, a more detailed analysis of exon 7 amplicons were performed followed by extensive cloning and Sanger sequencing. Interestingly, by comparing data from the pooled samples to the individually sequenced exon 7, we demonstrate that mutations are more easily recovered from WGA pools and this was also supported by simulations of different sequencing coverage. Overall this data indicate a limited random loss of genomic regions supporting the use of whole genome amplification for genomic analysis.

Using Whole-Exome Sequencing to Identify Genetic Markers for Carboplatin and Gemcitabine-Induced Toxicities.

PURPOSE: Chemotherapies are associated with significant interindividual variability in therapeutic effect and adverse drug reactions. In lung cancer, the use of gemcitabine and carboplatin induces grade 3 or 4 myelosuppression in about a quarter of the patients, while an equal fraction of patients is basically unaffected in terms of myelosuppressive side effects. We therefore set out to identify genetic markers for gemcitabine/carboplatin-induced myelosuppression. EXPERIMENTAL DESIGN: We exome sequenced 32 patients that suffered extremely high neutropenia and thrombocytopenia (grade 3 or 4 after first chemotherapy cycle) or were virtually unaffected (grade 0 or 1). The genetic differences/polymorphism between the groups were compared using six different bioinformatics strategies: (i) whole-exome nonsynonymous single-nucleotide variants association analysis, (ii) deviation from Hardy-Weinberg equilibrium, (iii) analysis of genes selected by a priori biologic knowledge, (iv) analysis of genes selected from gene expression meta-analysis of toxicity datasets, (v) Ingenuity Pathway Analysis, and (vi) FunCoup network enrichment analysis. RESULTS: A total of 53 genetic variants that differed among these groups were validated in an additional 291 patients and were correlated to the patients' myelosuppression. In the validation, we identified rs1453542 in OR4D6 (P = 0.0008; OR, 5.2; 95% CI, 1.8-18) as a marker for gemcitabine/carboplatin-induced neutropenia and rs5925720 in DDX53 (P = 0.0015; OR, 0.36; 95% CI, 0.17-0.71) as a marker for thrombocytopenia. Patients homozygous for the minor allele of rs1453542 had a higher risk of neutropenia, and for rs5925720 the minor allele was associated with a lower risk for thrombocytopenia. CONCLUSIONS: We have identified two new genetic markers with the potential to predict myelosuppression induced by gemcitabine/carboplatin chemotherapy.

Assessment of whole genome amplification for sequence capture and massively parallel sequencing.

Exome sequence capture and massively parallel sequencing can be combined to achieve inexpensive and rapid global analyses of the functional sections of the genome. The difficulties of working with relatively small quantities of genetic material, as may be necessary when sharing tumor biopsies between collaborators for instance, can be overcome using whole genome amplification. However, the potential drawbacks of using a whole genome amplification technology based on random primers in combination with sequence capture followed by massively parallel sequencing have not yet been examined in detail, especially in the context of mutation discovery in tumor material. In this work, we compare mutations detected in sequence data for unamplified DNA, whole genome amplified DNA, and RNA originating from the same tumor tissue samples from 16 patients diagnosed with non-small cell lung cancer. The results obtained provide a comprehensive overview of the merits of these techniques for mutation analysis. We evaluated the identified genetic variants, and found that most (74%) of them were observed in both the amplified and the unamplified sequence data. Eighty-nine percent of the variations found by WGA were shared with unamplified DNA. We demonstrate a strategy for avoiding allelic bias by including RNA-sequencing information.

Integrated molecular portrait of non-small cell lung cancers.

BACKGROUND: Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC. METHODS: Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC. RESULTS: At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1 and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of ~800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944. CONCLUSIONS: Integrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes.

Identification of candidate SNPs for drug induced toxicity from differentially expressed genes in associated tissues.

The growing collection of publicly available high-throughput data provides an invaluable resource for generating preliminary in silico data in support of novel hypotheses. In this study we used a cross-dataset meta-analysis strategy to identify novel candidate genes and genetic variations relevant to paclitaxel/carboplatin-induced myelosuppression and neuropathy. We identified genes affected by drug exposure and present in tissues associated with toxicity. From ten top-ranked genes 42 non-synonymous single nucleotide polymorphisms (SNPs) were identified in silico and genotyped in 94 cancer patients treated with carboplatin/paclitaxel. We observed variations in 11 SNPs, of which seven were present in a sufficient frequency for statistical evaluation. Of these seven SNPs, three were present in ABCA1 and ATM, and showed significant or borderline significant association with either myelosuppression or neuropathy. The strikingly high number of associations between genotype and clinically observed toxicity provides support for our data-driven computations strategy to identify biomarkers for drug toxicity.

Molecular Characteristics of ERCC1-Negative versus ERCC1-Positive Tumors in Resected NSCLC.

PURPOSE: Excision repair cross-complementation group 1 (ERCC1) is a protein involved in repair of DNA platinum adducts and stalled DNA replication forks. We and others have previously shown the influence of ERCC1 expression upon survival rates and benefit of cisplatin-based chemotherapy in patients with resected non-small-cell lung cancer (NSCLC). However, little is known about the molecular characteristics of ERCC1-positive and ERCC1-negative tumors. EXPERIMENTAL DESIGN: We took advantage of a cohort of 91 patients with resected NSCLC, for which we had matched frozen and paraffin-embedded samples to explore the comparative molecular portraits of ERCC1-positive and ERCC1-negative tumors of NSCLC. We carried out a global molecular analysis including assessment of ERCC1 expression levels by using both immunohistochemistry (IHC) and quantitative reverse transcriptase PCR (qRT-PCR), genomic instability, global gene and miRNA expression, and sequencing of selected key genes involved in lung carcinogenesis. RESULTS: ERCC1 protein and mRNA expression were significantly correlated. However, we observed several cases with clear discrepancies. We noted that ERCC1-negative tumors had a higher rate of genomic abnormalities versus ERCC1-positive tumors. ERCC1-positive tumors seemed to share a common DNA damage response (DDR) phenotype with the overexpression of seven genes linked to DDR. The miRNA expression analysis identified miR-375 as significantly underexpressed in ERCC1-positive tumors. CONCLUSIONS: Our data show inconsistencies in ERCC1 expression between IHC and qRT-PCR readouts. Furthermore, ERCC1 status is not linked to specific mutational patterns or frequencies. Finally, ERCC1-negative tumors have a high rate of genomic aberrations that could consequently influence prognosis in patients with resected NSCLC.