Monitoring of Technical Variation in Quantitative High-Throughput Datasets

Lauss, Martin; Visne, Ilhami; Kriegner, Albert; Ringnér, Markus; Jönsson, Göran; Höglund, Mattias

doi:10.4137/cin.s12862

Cited by 58 publications

(48 citation statements)

References 27 publications

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“…38) in the 1,398-sample cohort, including different clinicopathologic factors (gender, stage, clinical smoking status, EGFR and KRAS mutations), unsupervised gene expression clusters (see below), and molecular adenocarcinoma subtypes (26). Supporting the moderate supervised classification results, and the identification of a smaller set of smoking-related CNAs, we found that smoking status was not a dominant contributor to the total copy-number variation in the cohort (Supplementary Fig.…”

Section: Supervised Classification Of Smoking-related Cnassupporting

confidence: 49%

“…PCA analysis (38) performed in the TCGA RNAseq and Chitale and colleagues (32) gene expression microarray cohorts confirmed that clinical smoking status together with other clinicopathologic factors such as stage, gender, EGFR, and KRAS mutation status were not strong contributors to the total variation in gene expression compared with for instance reported adenocarcinoma subtypes (26; Supplementary Fig. S5).…”

Section: Smokers and Never-smokers Aggregating Together In Consensus mentioning

confidence: 99%

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Genomic and Transcriptional Alterations in Lung Adenocarcinoma in Relation to Smoking History

Karlsson

Ringnér

Lauss

et al. 2014

Clinical Cancer Research

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Purpose: Cigarette smoking is the major pathogenic factor for lung cancer. The precise mechanisms of tobacco-related carcinogenesis and its effect on the genomic and transcriptional landscape in lung cancer are not fully understood.Experimental Design: A total of 1,398 (277 never-smokers and 1,121 smokers) genomic and 1,449 (370 never-smokers and 1,079 smokers) transcriptional profiles were assembled from public lung adenocarcinoma cohorts, including matched next-generation DNA-sequencing data (n ¼ 423). Unsupervised and supervised methods were used to identify smoking-related copy-number alterations (CNAs), predictors of smoking status, and molecular subgroups.Results: Genomic meta-analyses showed that never-smokers and smokers harbored a similar frequency of total CNAs, although specific regions (5q, 8q, 16p, 19p, and 22q) displayed a 20% to 30% frequency difference between the two groups. Importantly, supervised classification analyses based on CNAs or gene expression could not accurately predict smoking status (balanced accuracies 60% to 80%). However, unsupervised multicohort transcriptional profiling stratified adenocarcinomas into distinct molecular subgroups with specific patterns of CNAs, oncogenic mutations, and mutation transversion frequencies that were independent of the smoking status. One subgroup included approximately 55% to 90% of neversmokers and approximately 20% to 40% of smokers (both current and former) with molecular and clinical features of a less aggressive and smoking-unrelated disease. Given the considerable intragroup heterogeneity in smoking-defined subgroups, especially among former smokers, our results emphasize the clinical importance of accurate molecular characterization of lung adenocarcinoma.Conclusions: The landscape of smoking-related CNAs and transcriptional alterations in adenocarcinomas is complex, heterogeneous, and with moderate differences. Our results support a molecularly distinct less aggressive adenocarcinoma entity, arising in never-smokers and a subset of smokers. Clin Cancer Res; 20(18); 4912-24. Ó2014 AACR.

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Section: Supervised Classification Of Smoking-related Cnassupporting

confidence: 49%

Section: Smokers and Never-smokers Aggregating Together In Consensus mentioning

confidence: 99%

Genomic and Transcriptional Alterations in Lung Adenocarcinoma in Relation to Smoking History

Karlsson

Ringnér

Lauss

et al. 2014

Clinical Cancer Research

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“…When preparing libraries for NGS sequencing, it is also critical to give consideration to the mitigation of batch effects (43–45). It is also important to acknowledge the impact of systematic bias resulting from the molecular manipulations required to generate NGS data; for example, the bias introduced by sequence-dependent differences in adaptor ligation efficiencies in miRNA-seq library preparations.…”

Section: Considerationsinngslibrary Preparation: Complexity Bias Anmentioning

confidence: 99%

Library construction for next-generation sequencing: Overviews and challenges

et al. 2014

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High-throughput sequencing, also known as next-generation sequencing (NGS), has revolutionized genomic research. In recent years, NGS technology has steadily improved, with costs dropping and the number and range of sequencing applications increasing exponentially. Here, we examine the critical role of sequencing library quality and consider important challenges when preparing NGS libraries from DNA and RNA sources. Factors such as the quantity and physical characteristics of the RNA or DNA source material as well as the desired application (i.e., genome sequencing, targeted sequencing, RNA-seq, ChIP-seq, RIP-seq, and methylation) are addressed in the context of preparing high quality sequencing libraries. In addition, the current methods for preparing NGS libraries from single cells are also discussed.

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“…13; Supplementary Materials and Methods). Principal component analysis (14), including clinicopathologic and technical factors, and comparison of bisulfite conversion plate and beadchip id against unsupervised bootstrap clusters were performed to assess that no technical artifacts influenced methylation data, or bootstrap groups, for the 124-sample discovery cohort ( Supplementary Fig. S1B-S1D).…”

Section: Global Methylation Analysismentioning

confidence: 99%

Genome-wide DNA Methylation Analysis of Lung Carcinoma Reveals One Neuroendocrine and Four Adenocarcinoma Epitypes Associated with Patient Outcome

Karlsson

Jönsson

Lauss

et al. 2014

Clinical Cancer Research

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Purpose: Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. However, whether clinically relevant subgroups based on DNA methylation patterns exist in lung cancer remains unclear.Experimental Design: Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 12 normal lung tissues and 124 tumors, including 83 adenocarcinomas, 23 squamous cell carcinomas (SqCC), 1 adenosquamous cancer, 5 large cell carcinomas, 9 large cell neuroendocrine carcinomas (LCNEC), and 3 small-cell carcinomas (SCLC). Unsupervised bootstrap clustering was performed to identify DNA methylation subgroups, which were validated in 695 adenocarcinomas and 122 SqCCs. Subgroups were characterized by clinicopathologic factors, whole-exome sequencing data, and gene expression profiles.Results: Unsupervised analysis identified five DNA methylation subgroups (epitypes). One epitype was distinctly associated with neuroendocrine tumors (LCNEC and SCLC). For adenocarcinoma, remaining four epitypes were associated with unsupervised and supervised gene expression phenotypes, and differences in molecular features, including global hypomethylation, promoter hypermethylation, genomic instability, expression of proliferation-associated genes, and mutations in KRAS, TP53, KEAP1, SMARCA4, and STK11. Furthermore, these epitypes were associated with clinicopathologic features such as smoking history and patient outcome.Conclusions: Our findings highlight one neuroendocrine and four adenocarcinoma epitypes associated with molecular and clinicopathologic characteristics, including patient outcome. This study demonstrates the possibility to further subgroup lung cancer, and more specifically adenocarcinomas, based on epigenetic/molecular classification that could lead to more accurate tumor classification, prognostication, and tailored patient therapy. Clin Cancer Res; 20(23); 6127-40. Ó2014 AACR.

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Monitoring of Technical Variation in Quantitative High-Throughput Datasets

Cited by 58 publications

References 27 publications

Genomic and Transcriptional Alterations in Lung Adenocarcinoma in Relation to Smoking History

Genomic and Transcriptional Alterations in Lung Adenocarcinoma in Relation to Smoking History

Library construction for next-generation sequencing: Overviews and challenges

Genome-wide DNA Methylation Analysis of Lung Carcinoma Reveals One Neuroendocrine and Four Adenocarcinoma Epitypes Associated with Patient Outcome

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