Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

Integrated Genomic Analysis of Hürthle Cell Cancer Reveals Oncogenic Drivers, Recurrent Mitochondrial Mutations, and Unique Chromosomal Landscapes.

Cancer cell | 2018

The molecular foundations of Hürthle cell carcinoma (HCC) are poorly understood. Here we describe a comprehensive genomic characterization of 56 primary HCC tumors that span the spectrum of tumor behavior. We elucidate the mutational profile and driver mutations and show that these tumors exhibit a wide range of recurrent mutations. Notably, we report a high number of disruptive mutations to both protein-coding and tRNA-encoding regions of the mitochondrial genome. We reveal unique chromosomal landscapes that involve whole-chromosomal duplications of chromosomes 5 and 7 and widespread loss of heterozygosity arising from haploidization and copy-number-neutral uniparental disomy. We also identify fusion genes and disrupted signaling pathways that may drive disease pathogenesis.

Pubmed ID: 30107176 RIS Download

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


Agilent Technologies (tool)

RRID:SCR_013575

Company provides laboratories worldwide with analytical instruments and supplies, clinical and diagnostic testing services, consumables, applications and expertise in life sciences and applied chemical markets.

View all literature mentions

HA-Tag (C29F4) Rabbit mAb (antibody)

RRID:AB_1549585

This monoclonal targets HA-Tag

View all literature mentions

MutSig (software resource)

RRID:SCR_010779

Software that analyzes lists of mutations discovered in DNA sequencing, to identify genes that were mutated more often than expected by chance given background mutation processes.

View all literature mentions

GATK (software resource)

RRID:SCR_001876

A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)

View all literature mentions

MuTect (software resource)

RRID:SCR_000559

Software for the reliable and accurate identification of somatic point mutations in next generation sequencing data of cancer genomes.

View all literature mentions

SomaticSniper (software resource)

RRID:SCR_005108

Software program to identify single nucleotide positions that are different between tumor and normal (or, in theory, any two bam files). It takes a tumor bam and a normal bam and compares the two to determine the differences. It outputs a file in a format very similar to Samtools consensus format. It uses the genotype likelihood model of MAQ (as implemented in Samtools) and then calculates the probability that the tumor and normal genotypes are different. This probability is reported as a somatic score. The somatic score is the Phred-scaled probability (between 0 to 255) that the Tumor and Normal genotypes are not different where 0 means there is no probability that the genotypes are different and 255 means there is a probability of 1 ? 10(255/-10) that the genotypes are different between tumor and normal. This is consistent with how the SAM format reports such probabilities. It is currently available as source code via github or as a Debian APT package.

View all literature mentions

Integrative Genomics Viewer (software resource)

RRID:SCR_011793

A high-performance visualization tool for interactive exploration of large, integrated genomic datasets.

View all literature mentions

FusionCatcher (software resource)

RRID:SCR_000060

Software that searches for novel/known fusion genes, translocations, and chimeras in RNA-seq data (paired-end reads from Illumina NGS platforms like Solexa and HiSeq) from diseased samples.

View all literature mentions