This tab shows an overview of the selected study/paper [more details]
Reference

The Mitochondrial and Autosomal Mutation Landscapes of Prostate Cancer.

Paper Id
COSP30596
Authors
Lindberg J,Mills IG,Klevebring D,Liu W,Neiman M,Xu J,Wikström P,Wiklund P,Wiklund F,Egevad L and Grönberg H
Affiliation
Department of Medical Epidemiology and Biostatistics, Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden.
Journal
European urology 2013;63(4):702-8
ISSN:1873-7560
PUBMED:23265383
Abstract
Background: Prostate cancer (PCa) is the most common cancer in men. PCa is strongly age associated; low death rates in surveillance cohorts call into question the widespread use of surgery, which leads to overtreatment and a reduction in quality of life. There is a great need to increase the understanding of tumor characteristics in the context of disease progression.Objective: To perform the first multigenome investigation of PCa through analysis of both autosomal and mitochondrial DNA, and to integrate exome sequencing data, and RNA sequencing and copy-number alteration (CNA) data to investigate how various different tumor characteristics, commonly analyzed separately, are interconnected.Exome sequencing was applied to 64 tumor samples from 55 PCa patients with varying stage and grade. Integrated analysis was performed on a core set of 50 tumors from which exome sequencing, CNA, and RNA sequencing data were available.Genes, mutated at a significantly higher rate relative to a genomic background, were identified. In addition, mitochondrial and autosomal mutation rates were correlated to CNAs and proliferation, assessed as a cell cycle gene expression signature.Genes not previously reported to be significantly mutated in PCa, such as cell division cycle 27 homolog (Saccharomyces cerevisiae) (CDC27), myeloid/lymphoid or mixed-lineage leukemia 3 (MLL3), lysine (K)-specific demethylase 6A (KDM6A), and kinesin family member 5A (KIF5A) were identified. The mutation rate in the mitochondrial genome was 55 times higher than that of the autosomes. Multilevel analysis demonstrated a tight correlation between high reactive-oxygen exposure, chromosomal damage, high proliferation, and in parallel, a transition from multiclonal indolent primary PCa to monoclonal aggressive disease. As we only performed targeted sequence analysis; copy-number neutral rearrangements recently described for PCa were not accounted for.Conclusions: The mitochondrial genome displays an elevated mutation rate compared to the autosomal chromosomes. By integrated analysis, we demonstrated that different tumor characteristics are interconnected, providing an increased understanding of PCa etiology.
Paper Status
Curated
Genes Analysed
2171
Mutated Samples
63
Total No. of Samples
63
This tab shows genes with mutations in the selected study/paper [more details]
Genes Samples CDS Mutation AA Mutation
This tab shows genes without mutations in the selected study/paper [more details]
Non-Mutant Genes Gene Id (COSG)
This tab shows samples without mutations in the selected study/paper [more details]
Non-Mutant Samples Sample Id (COSS)
This tab shows mutated samples in the selected study/paper [more details]
Sample Name Mutation Count
This tab shows non coding variant in the selected study/paper [more details]
Sample ID Sample Name ID NCV Annotation Zygosity Chromosome Genome start Genome stop Genome version Strand WT seq Mut seq
This tab shows the gene expression and copy number variation data for this study. [more details]

Table Information

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The table currently shows only high value (numeric) copy number data. Copy number segments are excluded if the total copy number and minor allele values are unknown.

Click here to include all copy number data. For more detailed information about copy number data and gain/loss definitions click here.

Sample Gene Expression Expr Level (Z-Score)

Over Expressed; Z-Score > 2.0

Under Expressed; Z-Score < -2.0

Normal; Z-Score within the range -2.0 to 2.0

CN Type Minor Allele Copy Number CN Segment Posn. Average Ploidy

1. N/A represents cases where the average ploidy value is not available( mostly ICGC samples). For some TCGA samples where the minor allele information is not available the average ploidy value could not be calculated.

2. For TCGA samples, the ASCAT algorithm was used to calculate the average ploidy.

3. For CGP samples, the PICNIC algorithm was used to calculate the average ploidy.

CNV
This tab shows a summary table with counts (number of samples) for CNV gain/loss and under/over expression for all genes. [more details]

The results shown in this table are derived from all copy number data. This includes non-numeric data with descriptive definitions of gain/loss.

  Copy Number Expression
Gene Gain Loss Tested Over Under Tested
This tab shows the fusion mutations observed in this sample [more details]
Gene Sample Name Id Sample(COSS) CDS Mutation Somatic status Zygosity Validated Type