Global analysis of somatic structural genomic alterations and their impact on gene expression in diverse human cancers

Tumor genomes are mosaics of somatic structural variants (SVs) that may contribute to the activation of oncogenes or inactivation of tumor suppressors, for example, by altering gene copy number amplitude. However, there are multiple other ways in which SVs can modulate transcription, but the general impact of such events on tumor transcriptional output has not been systematically determined. Here we use whole-genome sequencing data to map SVs across 600 tumors and 18 cancers, and investigate the relationship between SVs, copy number alterations (CNAs), and mRNA expression. We find that 34% of CNA breakpoints can be clarified structurally and that most amplifications are due to tandem duplications. We observe frequent swapping of strong and weak promoters in the context of gene fusions, and find that this has a measurable global impact on mRNA levels. Interestingly, several long noncoding RNAs were strongly activated by this mechanism. Additionally, SVs were confirmed in telomere reverse transcriptase (TERT) upstream regions in several cancers, associated with elevatedTERTmRNA levels. We also highlight high-confidence gene fusions supported by both genomic and transcriptomic evidence, including a previously undescribed paired box 8 (PAX8)–nuclear factor, erythroid 2 like 2 (NFE2L2) fusion in thyroid carcinoma. In summary, we combine SV, CNA, and expression data to provide insights into the structural basis of CNAs as well as the impact of SVs on gene expression in tumors.

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Interplay between copy number, dosage compensation and expression noise in Drosophila

10.1101/041038 ◽

2016 ◽

Author(s):

Dong-Yeon Cho ◽

Hangnoh Lee ◽

Damian Wojtowicz ◽

Steven Russell ◽

Brian Oliver ◽

...

Keyword(s):

Gene Expression ◽

Dose Reduction ◽

Dosage Compensation ◽

Copy Number ◽

Feedback Loops ◽

Gene Copy ◽

Gene Deletions ◽

Expression Variability ◽

Expression Noise ◽

The Impact

Gene copy number variations are associated with many disorders characterized by high phenotypic heterogeneity. Disease penetrance differs even in genetically identical twins. Can such heterogeneity arise, in part, from increased expression variability of one dose genes? While increased variability in the context of single cell gene expression is well recognized, our computational simulations indicated that in a multicellular organism intrinsic single cell level noise should cancel out and thus the impact of gene copy reduction on organismal level expression variability must be due to something else. To systematically examine the impact of gene dose reduction on expression variability in a multi-cellular organism, we performed experimental gene expression measurements in Drosophila DrosDel autosomal deficiency lines. Genome-wide analysis revealed that autosomal one dose genes have higher gene expression variability relative to two dose genes. In flies, gene dose reduction is often accompanied by dosage compensation at the gene expression level. Surprisingly, expression noise was increased by compensation. This increased compensation-dependent variability was found to be a property of one dose autosomal genes but not X-liked genes in males despite the fact that they too are dosage compensated, suggesting that sex chromosome dosage compensation also results in noise reduction. Previous studies attributed autosomal dosage compensation to feedback loops in interaction networks. Our results suggest that these feedback loops are not optimized to deliver consistent responses to gene deletion events and thus gene deletions can lead to heterogeneous responses even in the context of an identical genetic background. Additionally, we show that expression variation associated with reduced dose of transcription factors propagate through the gene interaction network, impacting a large number of downstream genes. These properties of gene deletions could contribute to the phenotypic heterogeneity of diseases associated with haploinsufficiency.

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Faculty Opinions recommendation of The impact of copy number variation on local gene expression in mouse hematopoietic stem and progenitor cells.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1158714.618930 ◽

2009 ◽

Author(s):

Michael Lassner ◽

Antoni Rafalski

Keyword(s):

Gene Expression ◽

Copy Number Variation ◽

Progenitor Cells ◽

Copy Number ◽

Hematopoietic Stem ◽

Stem And Progenitor Cells ◽

Number Variation ◽

The Impact

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Insulin-like Growth Factor Receptor 1 (IGF1R) Gene Copy Number Is Associated With Survival in Operable Non–Small-Cell Lung Cancer: A Comparison Between IGF1R Fluorescent In Situ Hybridization, Protein Expression, and mRNA Expression

Journal of Clinical Oncology ◽

10.1200/jco.2009.24.6611 ◽

2010 ◽

Vol 28 (13) ◽

pp. 2174-2180 ◽

Cited By ~ 89

Author(s):

Rafal Dziadziuszko ◽

Daniel T. Merrick ◽

Samir E. Witta ◽

Adelita D. Mendoza ◽

Barbara Szostakiewicz ◽

...

Keyword(s):

Gene Expression ◽

Growth Factor ◽

Protein Expression ◽

Squamous Cell ◽

Copy Number ◽

Gene Copy Number ◽

Growth Factor Receptor ◽

Gene Copy ◽

Cell Versus

PurposeThe purpose of this study was to characterize insulin-like growth factor-1 receptor (IGF1R) protein expression, mRNA expression, and gene copy number in surgically resected non–small-cell lung cancers (NSCLC) in relation to epidermal growth factor receptor (EGFR) protein expression, patient characteristics, and prognosis.Patients and MethodsOne hundred eighty-nine patients with NSCLC who underwent curative pulmonary resection were studied (median follow-up, 5.3 years). IGF1R protein expression was evaluated by immunohistochemistry (IHC) with two anti-IGF1R antibodies (n = 179). EGFR protein expression was assessed with PharmDx kit. IGF1R gene expression was evaluated using quantitative reverse transcription polymerase chain reaction (qRT-PCR) from 114 corresponding fresh-frozen samples. IGF1R gene copy number was assessed by fluorescent in situ hybridization using customized probes (n = 181).ResultsIGF1R IHC score was higher in squamous cell carcinomas versus other histologies (P < .001) and associated with stage (P = .03) but not survival (P = .46). IGF1R and EGFR protein expression showed significant correlation (r = 0.30; P < .001). IGF1R gene expression by qRT-PCR was higher in squamous cell versus other histologies (P = .006) and did not associate with other clinical features nor survival (P = .73). Employing criteria previously established for EGFR copy number, patients with IGF1R amplification/high polysomy (n = 48; 27%) had 3-year survival of 58%, patients with low polysomy (n = 87; 48%) had 3-year survival of 47% and patients with trisomy/disomy (n = 46; 25%) had 3-year survival of 35%, respectively (P = .024). Prognostic value of high IGF1R gene copy number was confirmed in multivariate analysis.ConclusionIGF1R protein expression is higher in squamous cell versus other histologies and correlates with EGFR expression. IGF1R protein and gene expression does not associate with survival, whereas high IGF1R gene copy number harbors positive prognostic value.

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Drug Repositioning Based on the Reversal of Gene Expression Signatures Identifies TOP2A as a Therapeutic Target for Rectal Cancer

Cancers ◽

10.3390/cancers13215492 ◽

2021 ◽

Vol 13 (21) ◽

pp. 5492

Author(s):

Robson Francisco Carvalho ◽

Luisa Matos do Canto ◽

Sarah Santiloni Cury ◽

Torben Frøstrup Hansen ◽

Lars Henrik Jensen ◽

...

Keyword(s):

Gene Expression ◽

Rectal Cancer ◽

Cancer Patients ◽

Copy Number ◽

Topoisomerase Ii ◽

Drug Repositioning ◽

Gene Copy ◽

Common Disease ◽

Topoisomerase Ii Inhibitors ◽

Gene Expression Signatures

Rectal cancer is a common disease with high mortality rates and limited therapeutic options. Here we combined the gene expression signatures of rectal cancer patients with the reverse drug-induced gene-expression profiles to identify drug repositioning candidates for cancer therapy. Among the predicted repurposable drugs, topoisomerase II inhibitors (doxorubicin, teniposide, idarubicin, mitoxantrone, and epirubicin) presented a high potential to reverse rectal cancer gene expression signatures. We showed that these drugs effectively reduced the growth of colorectal cancer cell lines closely representing rectal cancer signatures. We also found a clear correlation between topoisomerase 2A (TOP2A) gene copy number or expression levels with the sensitivity to topoisomerase II inhibitors. Furthermore, CRISPR-Cas9 and shRNA screenings confirmed that loss-of-function of the TOP2A has the highest efficacy in reducing cellular proliferation. Finally, we observed significant TOP2A copy number gains and increased expression in independent cohorts of rectal cancer patients. These findings can be translated into clinical practice to evaluate TOP2A status for targeted and personalized therapies based on topoisomerase II inhibitors in rectal cancer patients.

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Shared DNA-based copy number with divided methylation changes differentiate and clinically associate early stage pancreatic cancer tumors.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.3_suppl.434 ◽

2021 ◽

Vol 39 (3_suppl) ◽

pp. 434-434

Author(s):

Eva Chao ◽

Kyaw Lwin Aung ◽

Qi Xu ◽

William H. Matsui ◽

Jeanne Kowalski

Keyword(s):

Gene Expression ◽

Pancreatic Cancer ◽

Overall Survival ◽

Clinical Outcomes ◽

Copy Number ◽

Cancer Biology ◽

Early Stage ◽

Molecular Taxonomy ◽

Unmet Need ◽

Gene Copy

434 Background: There is no known molecular taxonomy of pancreatic cancer that can guide therapeutic strategies. Understanding the fundamental molecular mechanism underlying pancreatic cancer biology remains an unmet need. We explore the extent to which combinations of DNA-based molecular changes in copy number (CN) and methylation separate early stage PAAD tumors and associated with survival outcomes. Methods: We performed genome-wide combined cluster analyses on DNA-based CN and methylation changes using TCGA data. We examined cluster associations with clinical outcomes by comparing in months (mos), Kaplan--Meier estimated overall survival (OS) and disease-free interval (DFI) using a log-rank test. We performed additional comparisons among CN-Methylation derived clusters with respect to PAAD phenotypes. Results: Using 78 early stage pancreatic cancer tumors from TCGA with CN, methylation and clinical outcomes data, we identified two patient clusters with distinct gene copy number signatures that when combined with three methylation signatures, resulted in three additional clusters. Thus, the same gene CN signature, when combined with different methylation signatures, further differentiated tumors into sub-clusters with varying levels of associations with clinical outcome. Among them, analogous to current gene-expression based subtypes, we also identified an immune-rich subtype that was associated with improved overall survival (n=21, median OS=16mos; DFI=16mos), and an extracellular matrix (ECM)-rich with worse survival (n=19, median OS=12mos; DFI=8mos). Unlike previous expression subtypes, we identified another metabolic-enriched subtype with the same worse median OS and DFI, differentiated by methylation with the ECM-rich subtype. The improved OS cluster had a signature of CN neutral and increased methylation, while the poor cluster had a signature of CN gains and increased methylation among a set of genes distinct from the improved cluster. No significant differences in age, site, microsatellite instability and KRAS status among clusters were noted. Notably, in a multivariable model that included gene expression-based subtypes, only our DNA-level subtypes remained significantly associated with overall survival. Conclusions: While RNA-level changes often display large variations, DNA-level changes are more robust. Copy number changes appear to separate tumors into poor and improved prognosis clusters, while methylation appears to inform on the further separation of poor prognosis into various levels. A DNA-based molecular taxonomy for early stage pancreatic cancer could prove invaluable when used in combination with methylation-based circulating tumor DNA assays for clinical trial monitoring of tumor responses.

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Codon usage is an important determinant of gene expression levels largely through its effects on transcription

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1606724113 ◽

2016 ◽

Vol 113 (41) ◽

pp. E6117-E6125 ◽

Cited By ~ 122

Author(s):

Zhipeng Zhou ◽

Yunkun Dang ◽

Mian Zhou ◽

Lin Li ◽

Chien-hung Yu ◽

...

Keyword(s):

Gene Expression ◽

Codon Usage ◽

Important Determinant ◽

Mrna Translation ◽

Mrna Levels ◽

Protein Coding ◽

Expression Levels ◽

Highly Expressed Genes ◽

The Impact ◽

Gene Expression Levels

Codon usage biases are found in all eukaryotic and prokaryotic genomes, and preferred codons are more frequently used in highly expressed genes. The effects of codon usage on gene expression were previously thought to be mainly mediated by its impacts on translation. Here, we show that codon usage strongly correlates with both protein and mRNA levels genome-wide in the filamentous fungus Neurospora. Gene codon optimization also results in strong up-regulation of protein and RNA levels, suggesting that codon usage is an important determinant of gene expression. Surprisingly, we found that the impact of codon usage on gene expression results mainly from effects on transcription and is largely independent of mRNA translation and mRNA stability. Furthermore, we show that histone H3 lysine 9 trimethylation is one of the mechanisms responsible for the codon usage-mediated transcriptional silencing of some genes with nonoptimal codons. Together, these results uncovered an unexpected important role of codon usage in ORF sequences in determining transcription levels and suggest that codon biases are an adaptation of protein coding sequences to both transcription and translation machineries. Therefore, synonymous codons not only specify protein sequences and translation dynamics, but also help determine gene expression levels.

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Abstract 4908: Deep sequence analysis of the relationship between gene expression, CpG island methylation, and gene copy number in breast cancer cells

10.1158/1538-7445.am2011-4908 ◽

2011 ◽

Author(s):

Zhifu Sun ◽

Yan W Asmann ◽

Krishna R Kalari ◽

Brian Bot ◽

Jeanette E Eckel-Passow ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Copy Number ◽

Breast Cancer Cells ◽

Cpg Island ◽

Gene Copy Number ◽

Gene Copy ◽

Cpg Island Methylation ◽

The Relationship ◽

Deep Sequence Analysis

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Alternative splicing in plants

Biochemical Society Transactions ◽

10.1042/bst0360508 ◽

2008 ◽

Vol 36 (3) ◽

pp. 508-510 ◽

Cited By ~ 27

Author(s):

Craig G. Simpson ◽

Dominika Lewandowska ◽

John Fuller ◽

Monika Maronova ◽

Maria Kalyna ◽

...

Keyword(s):

Gene Expression ◽

Alternative Splicing ◽

Reverse Transcription ◽

Protein Function ◽

Mrna Levels ◽

Reverse Transcription Pcr ◽

Multiple Genes ◽

The Impact

The impact of AS (alternative splicing) is well-recognized in animal systems as a key regulator of gene expression and proteome complexity. In plants, AS is of growing importance as more genes are found to undergo AS, but relatively little is known about the factors regulating AS or the consequences of AS on mRNA levels and protein function. We have established an accurate and reproducible RT (reverse transcription)–PCR system to analyse AS in multiple genes. Initial studies have identified new AS events confirming that current values for the frequency of AS in plants are likely to be underestimates.

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